Keywords: Fault Detection and diagnosis in Manufacturing, Mechatronics in Manufacturing Processes, Intelligent Process Automation
Abstract: In metal cutting, chatter is an unstable dynamic response that can lead to poor machining quality and shorten tool life. If chatter can be detected in a shorter time, processing losses can be minimized. To achieve the goal of real-time data-driven detection, this research proposes and investigates the use of two-dimensional sensor data as images to train a chatter detection model in milling. The authors use bending moments measured by sensors embedded in the Smart Tool Holder (STH) system developed in and accelerometers mounted on the cutting spindle. The results show that models based on bending moment or acceleration are both effective, but the former has lower detection time delay.

Keywords: Mobile Robots, Sensor Integration, Data Fusion, Identification and Estimation in Mechatronics
Abstract: This study integrates IMU, odometry, and UWB positioning to enhance robot position estimation. An Extended Kalman Filter improves position accuracy, and an algorithm fuses sensor data with UWB information. Simulation results in ROS-Gazebo show enhanced position estimation compared to using UWB alone, enabling its utilization in shipyard welding. Future work involves implementing the algorithm on actual robots for navigation in shipyards.

Keywords: Actuators in Mechatronic Systems, Humanoid Robots, Service Robots
Abstract: In many robotic applications, high torque density and highly efficient actuators are crucial to manage high-torque movements without compromising mobility through added weight and size. Engineers traditionally design these actuators using electric motors combined with high-ratio speed reducers like harmonic and cycloidal drives, or lever arms, to generate the necessary torque. However, these setups often face limitations such as high cost, low efficiency, and non-backdrivability. At our lab, we are studying a novel high-gear-ratio transmission based on a Wolfrom planetary gear train, which achieves exceptional speed ratios (over 200:1) while maintaining energy efficiency superior to commercial solutions across the entire operating range.

Our previous work has demonstrated promising outcomes and confirmed the theoretical framework. Through this poster, we aim to present and discuss the results of our latest prototype. Initial tests reveal an efficiency exceeding 80% for a gear ratio of 222:1, a weight of only 650g, a repeatable peak torque of 80Nm, and a backdriving torque below 1Nm.

Keywords: Actuators, Flexible Manipulators and Structures
Abstract: In this study, a soft fabric-based bending actuator with an antagonistic structure is designed and tested. Easy to manufacture and to customise to a wide range of applications, the actuator can modulate its stiffness and bending angle independently, by individually controlling the pressure of internal and external bladders that work antagonistically.

Keywords: Actuators, Medical Robotics/Mechatronics, Control Application in Mechatronics
Abstract: In this research, we have developed a compact, efficient rotary series elastic actuator (SEA) module compatible with MRI environments, driven by velocity-sourced ultrasonic motors. Through a DoB-based controller tailored for velocity-sourced SEA, we demonstrate robust torque control for our SEA module against varying external impedance, crucial for medical procedures guided by MRI. Tests conducted in a 3 Tesla MRI scanner confirm the SEA's effectiveness, with quick response time (0.1 seconds) and minimal error in torque output (within 2% of peak torque). Our control system performs consistently well across various impedance scenarios, offering a significant improvement over traditional controllers, especially in low-impedance situations.

Keywords: Artificial Intelligence in Mechatronics, Technology Enabled Teaching of Mechatronics, Mechatronics-Enabled Teaching and/or Training
Abstract: This paper proposes a pool robot system (PRS) capable of detecting and locating pool balls using deep learning networks. U-Net and Mask R-CNN networks are used to extract ball features while solving issues such as glare, shadows, and noise in images. U-Net outperforms Mask R-CNN in terms of accuracy, detection time, and memory footprint, making it more suitable for real-time detection in edge computing. To validate the feasibility of PRS, experiments were conducted on a pool table. The trained model achieved a detection rate of 98.76%, with the robotic arm completing clearance in an average of 20 shots in seven games.

Keywords: Control Application in Mechatronics, Identification and Estimation in Mechatronics
Abstract: In the practical systems, many systems can be described as non-differentiable sandwiched dynamic systems, which implies a non-differentiable nonlinearity is sandwiched between two cascaded subsystems. Such a system imposes great challenging on the controller designs, because it is not possible to directly handle the non-differentiable unknown nonlinearity, and new approaches must be developed. As a case study, this paper will focus on the tracking control of gear transmission servo systems where a dead zone is sandwiched. It is well known that the dead-zone in gear transmission servo systems adversely affects system performance. The systems, characterized by unknown parameters including dead-zone parameters, become non-differentiable sandwiched fourth-order non-lower-triangular dynamic systems. Furthermore, such systems are frequently subject to uncertainties and external disturbances, potentially hindering convergence and leading to state divergence, thereby exacerbating the complexity of controller designs. A so-called block control framework is proposed by combining disturbance feedforward compensation control technique with extended state observer and dynamic surface control technique based on the results of the system identification. It is rigorously proved that the tracking error will converge to a bounded neighborhood of the origin, additionally, the ultimate bound can be made arbitrarily small by adjusting parameters. Finally, experiment results validate the efficacy of the proposed strategy.

Keywords: Control Application in Mechatronics, Sensor Integration, Data Fusion, Rehabilitation Robots
Abstract: Exoskeletons have the potential to greatly enhance en- durance during long, exhausting mobility tasks, how- ever, commercially available sensors like IMUs, used to measure body movement and muscle activation, are rigid and can cause discomfort when worn between the body and an exoskeleton system. Advances in soft sensor technology enable more comfortable movement measurement. Existing control approaches, even those using soft sensors, often rely on indirect subject walking gait pattern estimation methods like muscle activation detection and human preference optimization. These methods may lead to imprecise gait event estimation and require time-consuming optimization of the exoskeleton torque profile. Our proposed controller scheme utilizes solely lightweight, comfortable fabric sensors for kinematic measurements, directly estimating the user’s walking gait pattern. This proposed approach aims to reduce user effort by providing peak exoskeleton assistance at the foot push-off event.

Keywords: Data Storage Systems, Software Design for System Integration, Compuational Models and Methods
Abstract: Enhancing supply chain transparency and sustainability is crucial for corporate social responsibility and operational sustainability. However, traditional tracing systems face challenges like data opacity and tampering vulnerabilities, risking profits, reputation, and consumer trust. This study investigates a Hyperledger Fabric blockchain-based traceability platform. Results show that a consortium blockchain enhances traceability efficiency, ensures data authenticity, and improves information transparency, overcoming traditional system challenges. This approach also ensures compliance with environmental and social responsibilities, aiding in achieving ESG and SDGs objectives. Overall, this research provides insights into blockchain's role in enhancing supply chain transparency and sustainability.

Keywords: Design Optimization in Mechatronics, Control Application in Mechatronics, Modeling and Design of Mechatonic Systems
Abstract: The main purpose of this paper is to focus on the semiconductor production process. Using blockchain technology, a secure and tamper-proof recipe transmission process is designed to ensure that the recipe consistently maintains the experimental results after being uploaded by process engineers, reducing the occurrence of production errors caused by personnel mistakenly modifying recipes. This paper proposes incorporating secure hashing algorithms combined with blockchain into the recipe management system, updating blockchain data simultaneously when uploading recipes, and performing computations during the download process. By comparing the current recipe with the records in the blockchain and using binary tree algorithms to obtain a list of differential files, differential downloading is performed to reduce file transmission time and accelerate the production process.

Keywords: Human -Machine Interfaces, Novel Industry Applications of Mechatroinics, Robot Dynamics and Control
Abstract: A primary challenge in model-based control is handling model uncertainties, which can be addressed through robust control or adaptive control. Robust control uses a predefined nominal model to eliminate uncertainties, with the Disturbance Observer (DOB) being a popular method due to its simplicity and reliability. However, DOB is able to struggle with time-varying systems and requires an accurate nominal model, which can be time-consuming to design. Adaptive control, on the other hand, adjusts to real-time changes in the model using methods like the Parameter Adaptation Algorithm (PAA). While effective, PAA is able to suffer from inaccuracies due to its reliance on mathematical estimations and continuous computation. Each approach has its drawbacks: robust control ignores all changes in the actual model, while adaptive control is overly sensitive to changes. However, their limitations can complement each other. Real-time parameter estimation from PAA can reduce discrepancies of modeling error in DOB, while DOB can stabilize transient errors in PAA. This paper, therefore, proposes a fusion method of robust and adaptive control to process the model uncertainties, the Complementary Adaptive Robust Control (C-ARC), which combines the strengths of both robust and adaptive control. Using Recursive Least Squares (RLS) and signal filters such as low-pass filter and high-pass filter, C-ARC estimates parameter changes in real-time and avoids interference of DOB and PAA each other. By updating the estimated model, designed by estimated parameters, into the nominal model of DOB, decrease in is available and hence, increase performance of DOB, increase in cutoff frequency of the Q-filter, is available. Once the nominal model in DOB is updated, DOB estimates discrepancy between the real model and the estimated model as disturbance and by rejection of the estimated disturbance, the real model can be replaced into the estimated model from RLS. Additionally, to increase tracking performance, adding a proper feedforward controller such as the Perfect Tracking Controller (PTC) with the same model as the estimated model is utilized. The performance of C-ARC was validated through MATLAB simulations.

Keywords: Human -Machine Interfaces, Rehabilitation Robots, Virtual Reality and Human Interface
Abstract: Augmented reality brain-computer interfaces (AR-BCIs) can be used to control a robot using a goal selection paradigm. As some users may prefer more manual control, we developed an AR-BCI for continuous control of robot translation, which we tested in a robotic reaching experiment. To improve performance, we developed a shared control system that significantly improved task success rate (paired two-tailed t-test, p<0.001, mean = 36.1%, 95% CI [25.3%, 46.9%]).

Keywords: Human -Machine Interfaces, Tele-operation, Sensors and Sensing Systems
Abstract: Recent advancements in equipment have highlighted their role in enhancing nursing care and preventing the transmission of diseases like COVID-19, sparking interest in remotely operating electric wheelchairs. Most current electric wheelchairs use infrared or electromagnetic waves, risking interference with human bodies and sensitive devices. This study introduces a remote control system for electric wheelchairs using harmless omnidirectional visible light communication (OVLC) through a Light Emitting Diode (LED) array and an omnidirectional camera that captures signal patterns without needing precise alignment. However, challenges such as resolution loss and image distortion arise with the omnidirectional camera, impacting signal decoding accuracy. To address these, we developed an AI-based technique that accurately recognizes and decodes LED patterns from a distance, enabling successful remote control of an electric wheelchair with our novel visible light teleoperation system.

Keywords: Control Application in Mechatronics, Parallel Mechanisms, Modeling and Design of Mechatonic Systems
Abstract: In this work, a gray-box-model-based control structure is proposed, with the retained inertial dynamics are directly derived by the principle of virtual work and the other parts are estimated by adaptive neural networks. This ensures calculation efficiency and integrity of the dynamics. Moreover, a prescribed performance function is constructed to ensure the specified tracking requirements both in transient and steady states. On the basis, the robust integral of signum of error term is incorporated to compensate the structural and unstructural uncertainties, which further improves the robustness during high-frequency motion. Comparative real-time experiments have been performed on the actual robot with attainment of the predefined performance.

Keywords: Educational Testbeds and/or Platforms, Sensors and Sensing Systems, Control Application in Mechatronics
Abstract: This project focuses on the development of a scale model luffing jib tower crane for the Crane Safety Research Center. A luffing jib tower crane is a modern design which is gaining popularity for its advantage in urban construction sites. The luffing motion gives them more versatility than traditional tower cranes and allows for the jib to be stowed vertically for a minimal footprint. These come with the trade-offs that they are more expensive and require more maintenance. Despite their increase in use, there has not been much research done on this style of crane when compared with standard tower cranes. This scale model is being designed with the goal of conducting research which can identify the parameters that lead to cranes tipping over and model the dynamics and control of luffing motion in modern cranes. The purpose of this crane is to provide hardware on which students and researchers can study dynamics and test out controls. As such, the crane should utilize common mechatronics components and software for ease of use and maintenance. This enables the crane to be used to study both luffing motion and tip over conditions. The crane will be used in experiments which will require it to move through its 3 axes of motion in a fixed position, as well as safely tip over and fall. In addition to this, other sensors may be needed to track the tip over angle and speed. This model will need to be designed for safe tip over in a small lab area. From these needs, an emphasis is placed on modularity, aesthetics, serviceability, and durability. This novel use of a safe tip-over catch mechanical for scale crane models requires validation through testing. On a smaller prototype model multiple mechanisms will be implemented to lock the tower section vertically, catch the fall of the tower section, and collect sensor data on the tip-over behaviour. The three leading designs for this mechanism are a set of adjustable legs mounted to the base, a vertical pipe section, and a hooped basket to catch the tower at a specific angle. These mechanisms can be installed with a sensored gimbal to track the fall of the tower section. These versions will be evaluated to select the best mechanism to be scaled up for the model crane.

Keywords: Machine Vision, Identification and Estimation in Mechatronics, Control Application in Mechatronics
Abstract: The goals of this project are to better understand crane tip-over accidents and to advance research to improve crane safety. Crane accidents occur at a large scale with varied conditions, so analyzing real accidents is important to reveal accident causes and key behaviors during accidents. Many videos of crane tip-over accidents have been published online, and by using video analysis tools, the behavior of these tip-overs can be quantified. Results from the video analysis have also been used to develop and validate a dynamic model of crane tip-over events that can be used to further explore tip-over behavior.

Video analysis of crane tip-over accidents is often made difficult by the relatively lower quality videos of accidents available on the Internet. Most videos appear to be shot with a handheld mobile phone; this is due to crane tip-over accidents happening without warning, and when videos of accidents are captured it is often by bystanders filming by happenstance. Common issues include low resolution, shaky video, poor contrast, and moving camera position. All these factors make it difficult to track objects in the video and extract meaningful data.

A video analysis process has been developed using Adobe After Effects and MATLAB to track and analyze objects in such accident videos. This process is used to extract and analyze the crane boom angle and angular speed over time during tip-over accidents. The sophisticated object tracking tools available in Adobe After Effects, which can dynamically adjust for changing brightness and contrast, are used to track specific points on the crane boom and to establish a fixed horizon line. Then, the MATLAB image processing toolbox is used to track these points, fit lines through the boom and horizon points, and calculate the relative angle between these two lines for each video frame to obtain the tip-over angle vs. time.

The process has been applied to several videos of mobile crane tip-over accidents to extract the angle and angular speed of the boom during the tip-over, identify the effects of key events that occur during these accidents, and to obtain an estimate of the total tip-over time of each accident.

Keywords: Modeling and Design of Mechatonic Systems, Learning and Neural Control in Mechatronics, Mobile Robots
Abstract: The concept of utilizing a modular version of the two-wheeled self-balancing robot is motivated by the need for modern robotic systems to be scalable, making it possible to build robots of various sizes and capabilities by adding or removing modules, redundant in the case of system failure, and reconfigurable and customizable for industries with unique requirements, such as manufacturing, healthcare, and agriculture [1]. With this change comes the added complexity of dealing with a high degree of parametric uncertainty due to variations in parameters like mass, friction, and center of gravity. This necessitates the design of a control system capable of overcoming these issues and so model-free reinforcement learning (RL) is investigated for this purpose [2].

Keywords: Novel Industry Applications of Mechatroinics, Service Robots
Abstract: Wheeled mobile service robots are increasingly used in restaurants, factories, and homes in various ways. Currently, autonomous mobile robots are used to move heavy weight goods to specific points in industrial environments such as factories. In everyday life, it is widely applied in the personal service sector, such as delivery service. This study proposes a wheel mechanism based on a joint link. We propose a step-up wheels that show the ability to overcome steps higher than the wheel diameter of a mobile robot through vertical force conversion. The concept of link-based reaction step-up wheels mechanism is introduced, and the constraints and design variables reviewed in the system configuration are examined. The mobile robot's ability to climb high step is improved by converting drive into vertical force using sub-wheels connected to the manual joints of the wheels. By delivering the body of the wheel drive robot through the converted vertical reaction force, the ability to climb steps is improved using the reaction force of the steps. The kinematic analysis and optimized design variables according to the link configuration and constraints of the wheel system are described. The vertical force required to lift the robot to the ground is maximized through the optimized variables. It provides the driving force and simulation data necessary to overcome the steps of the mobile robot through the previous analysis process. Experiments were conducted in various environments to prove the ability to overcome steps through prototype robot production. In conclusion, it was confirmed that the improvement of the step-overcoming performance was confirmed by changing the horizontal passive force of the robot generated during driving to vertical force

Keywords: Sensors and Sensing Systems, Sensor Integration, Data Fusion, Actuators
Abstract: Static and mobile sensor nodes can be employed in gas monitoring tasks to detect gas leaks in an early stage and localize gas sources. Due to the intermittent nature of gas plumes and the slow dynamics of commonly used gas sensors, measuring gas concentrations accurately and timely poses significant challenges. These challenges are exacerbated when measurements are gathered while moving. Actively sniffing in the airflow, facilitated by actuators, holds the potential to improve the quality of measurements obtained by the sensor nodes. In this paper, we present the design of a small-scale, modular sensor node endowed with gas and wind sensing modalities. To assess the benefits of active sampling and the rationale behind this enhancement, comparisons among three different air sampling modes in both static and mobile settings are conducted. Our findings suggest that passive sampling can adequately capture the primary features of gas plumes given sufficient exposure and measuring time at each position. However, active sampling enhances the responsiveness of sensor nodes, enabling the detection of more detailed fluctuations in the gas concentration and thus alleviating spatial shifts in the sensor response induced by mobility effects.

Keywords: Control Application in Mechatronics, Identification and Estimation in Mechatronics, Motion Vibration and Noise Control
Abstract: The high-speed operation of the stacker crane used in automated storage and retrieval systems is important for improving the efficiency of the entire warehouse. However, to achieve high-speed operation, it is necessary to reduce the excessive natural vibrations that occur during operation. To address this problem, this study proposes a vibration suppression feedforward control for an active mass damper (AMD). The objective of the proposed control method is to match the carriage acceleration of the stacker crane with the travel unit acceleration to avoid excessive vibrations in the stacker crane. This study introduces a method to realize this feedforward control and experimentally evaluates the performance of the proposed method using a test bench machine of a stacker crane.

Keywords: Actuators in Mechatronic Systems, Modeling and Design of Mechatonic Systems, Sensors and Sensing Systems
Abstract: This paper presents a 3DOF planar magnetic pantographic exoskeleton (Mag-PGE) with embedded sensors for manipulating/measuring the motion and force/torque (F/T) of an ankle joint in the sagittal plane. A biomimetic ankle-foot simulator (AFS) is designed to facilitate investigation and help visualize its potential uses for in-bed acute stroke rehabilitation where the affected leg muscles are often passive. Unlike a conventional motor in which the rotor is supported by mechanical bearings on the stator, the (stator, rotor) of the Mag-PGE are separately attached to the (shank, foot) sharing the ankle joint of the human leg such that it enables the foot to flex in the sagittal plane, imposing no mechanical constraints on the ankle-foot. A Mag-PGE/AFS model with closed-form solutions to the rotor magnetic field and motor F/T is provided; both forward and inverse problems are considered. The methods to design, train, and calibrate embedded sensors utilizing the rotor magnetic field to measure the rotor/foot motion are numerically and experimentally evaluated. As illustrated with an AFS, the model along with the embedded measurements plays a pivotal role in computing the forward and inverse solutions to the 3DOF motor force-current model.

Keywords: Modeling and Design of Mechatonic Systems, Sensors and Sensing Systems, Flexible Manipulators and Structures
Abstract: Soft robots, with their remarkable advantages in various applications, face the critical challenge of embodied perception, encompassing proprioceptive sensing and perceiving unknown environments (exteroception). In this paper, we achieve simultaneous continuous shape reconstruction and external force estimation for soft bending actuators using only a proprioceptive curvature sensor. We introduce a novel distributed inductive curvature sensor designed for capturing continuous shape through electromagnetic induction. Additionally, we enhance an analytical static model based on the Euler-Bernoulli curved beam theory to predict the shape under pneumatic actuation and external forces. Furthermore, a model-based optimization algorithm is proposed to estimate external forces based on the measured shape. Extensive experimental validation supports the efficacy of the proposed sensor and algorithms.

Keywords: Flexible Manipulators and Structures, Actuators
Abstract: Multistable structures, known for their ability to rapidly switch between multiple stable states, are increasingly used for various robotic and mechatronic systems (e.g., grippers, swimming, jumping, or crawling robots). However, existing multistable structures generally have a fixed structure after fabrication, leading to a fixed energy profile with respect to deformations, a concept termed as energy landscape (EL) that dictates a structure's stable configurations and dynamic responses. To overcome this limitation, this work investigates how to actively tune the EL of a beam-based mechanism with a linear spring on the fly to enable tunable modules. We consider two tuning strategies to adjust the beam's initial bending angle and the offset of the spring. We establish a forward model to predict the module's EL and conduct experiments to validate this model. We also address the inverse problem to achieve a desired EL by choosing proper values of the initial bending angle and the offset of the spring. Finally, we demonstrate the practical applications of this tunable module with three cases: a kicker, a configurable arm, and a crawling robot. Our research lays the groundwork for advanced robotic and mechatronic systems, enabling them to harness structures with elastic instabilities for tuning their performance on the fly, thereby enhancing their adaptability and functionality.

Keywords: Control Application in Mechatronics
Abstract: Switched Reluctance Motors (SRMs) are widely used for their simplicity and cost-effectiveness, for example, in coarse laser pointing for free-space optical (FSO) communication, with torque ripple being a challenge in their implementation. This paper introduces an automated, model-free approach to minimize torque ripple in SRMs despite manufacturing variations. Using an extremum-seeking approach, the commutation parameters are adapted online to mitigate the position-dependent velocity ripple through gradient descent. Simulations show that the method's effectiveness is consistent across different SRMs, rendering it applicable to mass production, and experimental results verify that torque ripple is almost entirely eliminated in several hours. The developed approach enables accurate SRM control with minimal expert knowledge, functioning as a crucial step toward their deployment in constellation projects for FSO communication.

Keywords: Flexible Manipulators and Structures, Parallel Mechanisms, Novel Industry Applications of Mechatroinics
Abstract: This article proposes a novel compliance compensator that can measure six-axis force, torque and displacement. The proposed device can provide the information necessary for feedback control while protecting the robot from impact. The device was designed based on a 6-DOF parallel mechanism to have six-axis sensing and deform greatly at the rated load without failure. We designed new flexure links with flexure joints connected in series, which facilitates fabrication and stiffness analysis. Through the stiffness analysis, the measured force can be converted to displacement and the stiffness of the device can be customized to the desired value by simply adjusting the thickness of the links. The sensing performance was evaluated through experiments using a commercial force/torque sensor (F/T sensor) and precision stages. We also propose a displacement-based misalignment compensation method in a robotic peg-in-hole assembly using the proposed device. The method uses the intrinsic passive compliance of the device and measured displacement, not the force and torque. We reduced the reaction force generated in the peg-in-hole assembly by 92.6% through the proposed method. The proposed method is simple and intuitive, and can be used for automatic teaching of the manipulator.

Keywords: Flexible Manipulators and Structures, Sensors and Sensing Systems, Robot Dynamics and Control
Abstract: This article presents the design of a noncollocated feedback system for flexible serial manipulators. The device is a passive serial chain of encoders and lightweight links, mounted in parallel with the manipulator. This measuring arm effectively decouples the manipulator's proprioception from its actuators by providing information on the actual end effector pose, accounting for both joint and link flexibility. The kinematic redundancy of the measuring chain allows for safe operation in the context of human–robot interaction. A simple yet effective error model is introduced to assess the suitability of the proposed sensor system in the context of robotic control. The practicality of the device is first demonstrated by building a physical joint-encoder assembly and a simplified planar measuring arm prototype. With this additional feedback, a task-space position controller is devised and tested in simulation. Finally, the simulation results are validated with an experimental 3-DoF lightweight manipulator prototype equipped with a five-joint measuring arm.

Keywords: Flexible Manipulators and Structures, Fixture and Grasping, Rapid Prototyping
Abstract: Fine assembly tasks, such as electrical connector insertion have tight tolerances and sensitive components, requiring compensation of alignment errors while applying sufficient force in the insertion direction, ideally at high speeds and while grasping a range of components. Vision, tactile, or force sensors can compensate alignment errors, but have limited bandwidth, limiting the safe assembly speed. Passive compliance, such as silicone-based fingers can reduce collision forces and grasp a range of components, but often cannot provide the accuracy or assembly forces required. To support high-speed mechanical search and self-aligning insertion, this article proposes monolithic additively manufactured fingers which realize a moderate, structured compliance directly proximal to the gripped object. The geometry of finray-effect fingers are adapted to add form-closure features and realize a directionally dependent stiffness at the fingertip, with a high stiffness to apply insertion forces and lower transverse stiffness to support alignment. Design parameters and mechanical properties of the fingers are investigated with finite element method (FEM) and empirical studies, analyzing the stiffness, maximum load, and viscoelastic effects. The fingers realize a remote center of compliance, which is shown to depend on the rib angle, and a directional stiffness ratio of 14–36. The fingers are applied to a plug insertion task, realizing a tolerance window of 7.5 mm and approach speeds of 1.3 m/s.

Keywords: Sensors and Sensing Systems, Sensor Integration, Data Fusion, Modeling and Design of Mechatonic Systems
Abstract: Contact force sensing is necessary for robots to safely grasp and improve walking performance. Motivated by the linkage-type geometry of robotic fingers and legs, this article realizes contact force sensing on the L-shaped structure without additional force sensors. The lever-type method of strain exposure (LTMSE) is developed to enhance the force-sensing performance. This method is able to reduce the coupling in three-axis force measurement and improve the tradeoff (between sensitivity and stiffness). Further decrease of the coupling is accomplished via appropriate strain-gauge arrangement and static decoupling algorithms. The experimental results have demonstrated the force sensing performance of the L-shaped structure and verified the feasibility of the LTMSE for three-axis force measurement. The proposed design has potential applications in linkage-shaped robotic fingers, legs, and probes.

Keywords: Control Application in Mechatronics, Robot Dynamics and Control, Identification and Estimation in Mechatronics
Abstract: In precision assembly, a peg is guided into a hole with a tolerance smaller than the position accuracy. Although force/torque sensing can estimate the relative position between the peg and hole accurately, its performance is impaired because of the degradation of estimation accuracy caused by transient error at the time of the collision. We found in this study that if contact state transitions can be generated reproducibly, accurate relative positions can be derived from the transient responses, which were previously regarded as errors. We propose a method that focuses on this characteristic. The transition in the contact state is determined by force/torque responses. Then, the estimation accuracy of the direction of the hole improves by using only the force/torque responses of a specific contact state. Additionally, the time between the contact and estimation of the relative position is reduced by using the transient force information.

Keywords: Mobile Robots, Identification and Estimation in Mechatronics, Vehicle Technology
Abstract: As Autonomous Mobile Robots (AMRs) play an increasingly crucial role in logistics and service industries, their ability to navigate indoor and outdoor environments becomes paramount. A significant challenge lies in ensuring the effective entry of AMRs into buildings, mainly via the accessible ramps. This paper proposes an innovative method that empowers our two-wheeled self-balancing AMR to localize and navigate accessible ramps using solely RGB inputs for environmental assessment. Our model-free, behavior-reflex navigation approach harnesses deep learning-based object detection to identify and assess critical environmental elements for precise navigation control. A three-stage cascaded navigation strategy is proposed to ensure effective navigation for AMRs approaching the ramp from various directions and poses. Fuzzy mechanisms are devised to eliminate detection outliers and enhance accuracy, while a data history control scheme manages occasions when features are out of sight. Field experiments validated the effectiveness of our approach, demonstrating an average mission accomplishment rate of over 90%.

Keywords: Mobile Robots, Transportation Systems, Actuators in Mechatronic Systems
Abstract: Tough unmanned ground vehicles (UGVs) ordinally move on level grounds. However, several types of tough UGVs have been designed and developed for locomotion on uneven grounds. They are employed in agricultural robots, disaster robots, and robots used for hazardous applications. Especially, semi-active damping elements are one of the smart structures and potential solutions for highly stable locomotive robots. In this study, we propose a vibration control unit with a Magnetorheological Fluid (MRF)-based semi-active universal joint (SAUJ) for stable delivery equipment that can be attached to a UGV operating on uneven ground. The basic structure and controller of the SAUJ are proposed. In addition, its performance is experimentally evaluated on the ground and a moving UGV. According to the experimental results, vibration control of the SAUJ successfully decreased the perturbation of a pendulum swing due to the acceleration of the UGV.

Keywords: Mobile Robots, Planning and Navigation, Image Processing
Abstract: In Monocular Keyframe Visual Simultaneous Localization and Mapping (MKVSLAM) frameworks, when incremental position tracking fails, global pose has to be recovered in a short-time window, also known as short-term relocalization. This capability is crucial for mobile robots to have reliable navigation, build accurate maps, and have precise behaviors around human collaborators. This paper focuses on the development of robust short-term relocalization capabilities for mobile robots using a monocular camera system. A novel multimodal keyframe descriptor is introduced, that contains semantic information of objects detected in the environment and the spatial information of the camera. Using this descriptor a new Keyframe-based Place Recognition (KPR) method is proposed that is formulated as a multi-stage keyframe filtering algorithm. This leads to a new relocalization pipeline for MKVSLAM frameworks. The proposed approach is evaluated over several indoor GPS-denied datasets and demonstrates accurate pose recovery, in comparison to a bag-of-words approach

Keywords: Mobile Robots, Robot Dynamics and Control
Abstract: Both mobile robots and robotic arms provide valuable capabilities in a variety of industries, from the ability of robotic arms to perform manipulation tasks accurately and repeatably in manufacturing environments, to the autonomous navigation capabilities of mobile robots deployed in myriad dynamic and changing environments. Combining the navigation capabilities of mobile robots with the manipulation abilities of robotic arms further expands the application areas of robotics, and integrated control of such a mobile robotic arm improves the manipulation capabilities beyond that of a static robotic arm by increasing the XY working field of the arm and allowing for smoother, more energy-efficient trajectories. We propose a many-objective optimization-based method of online trajectory generation for integrated control of a mobile robot arm. We focus on trajectory generation to a specified end-effector configuration in an obstacle-free environment, with the main contribution being a method of generating trajectories for a differential-drive-based mobile robot arm by coordinating wheel joint and arm joint motions. Both offline and real-time simulated trials demonstrated a 100% success rate in reaching the desired end-effector configuration. Furthermore, the mobile robot arm was able to reach the desired configuration in <30s in 73% of the trials, and <60s in 94% of the trials, demonstrating the efficiency of the trajectories generated in real-time using this method.

Keywords: Mobile Robots, Sensors and Sensing Systems, Rehabilitation Robots
Abstract: In this paper, we propose an add-on electric drive system for manual wheelchairs using one active caster, which has been the driving wheel developed for omnidirectional robots. Active casters can instantly generate a velocity vector in any direction by the cooperative control of two motors. The active-caster is installed at the rear of a manual wheelchair to control the two degrees of freedom of the wheelchair movements: forward movement and turning. Furthermore, a torque detection system is installed into the power transmission of the active caster to measure the direction and magnitude of an applied force acting on the wheel. A power assist control of the wheelchair is performed based on this force detection. Therefore, there is no need to install any force detection devices on a manual wheelchair, it is possible to create wheelchair motions with electric motor support by applying force to any part of the wheelchair. This makes it possible for the wheelchair to be moved by pushing and pulling the wheelchair by a caregiver, by operating the large wheels by the passenger himself, by pushing the floor with his legs, or by pushing and pulling the desk with his hands. We demonstrate the feasibility of these functions through experiments using a prototype wheelchair.

Keywords: Mobile Robots, Planning and Navigation, Automotive Systems
Abstract: Exploration strategies of ground robots are often applied in indoor structured environments. However, numerous challenges persist in outdoor 3D unstructured environments, particularly in rough and rugged terrains. This paper proposed an autonomous exploration framework (SFRE) for ground mobile robots in uneven environments. The realization of SFRE can be broken down into three stages. First, the 2D traversability grid map is obtained by analyzing the terrain features of 3D uneven environments. Second, to improve exploration efficiency, we partition the exploration space and utilize the sparrow search algorithm to determine the visit order of each subspace. Finally, to ensure that the robot explores unknown regions safely, a new frontiers selection criterion that combines the height and slope of the frontiers is proposed, which has not been considered in previous methods for frontiers selection. Experiments are conducted to validate the safety and high efficiency of the proposed autonomous exploration framework. All tests show a reduction of 27% in exploration time and 32% in traveling distance compared to the comparative method. (Supplemented video link: https://youtu.be/-eVXv8Zx6VA)

Keywords: Actuators in Mechatronic Systems, Actuators
Abstract: Precise modeling soft robots remains a challenge due to their infinite-dimensional nature governed by partial differential equations. This paper introduces an innovative approach for modeling soft pneumatic actuators, employing a nonlinear framework through data-driven parameter estimation. The research begins by introducing Ludwick's Law, providing an accurate representation of the large deflections exhibited by soft materials. Three key material properties, namely Young's modulus, tensile stress, and mixed viscosity, are utilized to estimate the parameters inside the nonlinear model using the least squares method. Subsequently, a nonlinear dynamic model for soft actuators is constructed by applying Ludwick's Law. To validate the accuracy and effectiveness of the proposed method, several experiments are performed demonstrating the model's capabilities in predicting the dynamic behavior of soft pneumatic actuators. In conclusion, this work contributes to the advancement of soft pneumatic actuator modeling that represents their nonlinear behavior.

Keywords: Actuators in Mechatronic Systems, Actuators, Modeling and Design of Mechatonic Systems
Abstract: Embodying intelligence in soft robots requires the design of logic circuits that do not rely on electrical components. Previous research has shown that it is possible to achieve logic gates that rely solely on rigid or even soft mechanical parts. Here, we present a purely mechanical system that can reversibly switch between two mechanical configurations of the logic gates AND and OR upon triggering by a meta-input. In addition, we present the first gripper with such a variable logic gate. Since the whole mechanism is mechanical, including the meta-input, this is a new breakthrough for robotics applications in environments where electrical circuits are unsuitable.

Keywords: Actuators in Mechatronic Systems, Actuators, Identification and Estimation in Mechatronics
Abstract: This paper presents a comparative analysis of hybrid reluctance actuators (HRAs), one with a solid core and a version with a layered core, respectively. The dynamic performance is evaluated by employing flux control and current control for both actuators. With flux control, the phase lag caused by eddy current diffusion in the solid yoke HRA is reduced by 41° at the suspension mode as compared to current control. This enables the implementation of a cascaded control structure, with H-infinity position control reaching a closed-loop bandwidth of 750 Hz for the solid core HRA, similar to the conventional approach using a current-controlled laminated actuator. This offers the optionto dispense yoke lamination in favor of easier manufacturing and increased yoke fill factor.

Keywords: Actuators in Mechatronic Systems, Actuators, Identification and Estimation in Mechatronics
Abstract: In this paper, the dynamics of hybrid reluctance actuators (HRAs) are investigated by conducting dynamic force measurements on two HRAs, one with a laminated core and one with a solid core. The performance of current-controlled HRAs is limited by a frequency-dependent force-to-current relationship (FCR), which leads to a higher current demand for a constant force generation at higher frequencies due to eddy current diffusion in the stator yoke. The FCR is further depending on the amplitude of the driving signal due to hysteresis. Flux feedback control on the other hand can realise a largely frequency-independent flux-to-force relationship (FFR) up to 1 kHz for both a solid and a laminated core actuator. The force dynamics are evaluated in the frequency domain and the power consumption for positioning applications is compared for a current-controlled layered core and a flux-controlled solid core HRA, showing an increased power consumption by a factor of six in the latter case.

Keywords: Actuators in Mechatronic Systems, Modeling and Design of Mechatonic Systems, Flexible Manipulators and Structures
Abstract: This paper presents the design concept of a soft continuous permanent magnet (C-PM) and magnetic elasticity for the design and control of a magnetic series elastic actuator (Mag-SEA). Unlike a conventional SEA typically designed by integrating an elastic element into an actuator through a mechanical leadscrew (Mech-LS), there is no physical contact between the rotor and translator of a Mag-SEA where their “gap” plays the role of a noncontact “magnetic spring” as the rotor magnetically drives the translator like a LS through helical PMs. Using a distributed current source (DCS) method verified with analytical solutions and finite element analyses, the magnetic force vector of a Mag-SEA built with C-PM is derived and evaluated by comparing it with that designed with cylindrical PMs to approximate the helical PMs. With the magnetic elasticity computed using the DCS method and a control-oriented perturbation model, the parametric effects on the dynamics and stability are investigated numerically to gain insights into the plant characteristics of a Mag-SEA.

Keywords: Actuators in Mechatronic Systems, Design Optimization in Mechatronics
Abstract: Permanent magnet linear synchronous motors (PMLSM) are widely implemented in precision manufacturing equipment with the advantages of high efficiency and high positioning accuracy. However, the thrust density of the coreless-type PMLSM is small. Due to the existence of processing errors, there is a certain gap between the actual production of the motor and the theoretical design of the motor performance, especially the winding error on the thrust ripple. Aiming at the above problems, this paper proposes a structure of a new PCB coreless-type PMLSM. This structure ensures high accuracy in coil positioning and greatly reduces costs in the manufacture of motors' actuators. In addition, this motor structure is capable of large electromagnetic thrust within the size constraints of high precision equipment. To this end, this paper presents a three-dimensional structure and analytical model of a new PCB coreless-type PMLSM. Optimization of structural parameters based on response surface method to improve motor performance. The effectiveness of the method is demonstrated by comparing the performance of the motor before and after optimization.

Keywords: Artificial Intelligence in Mechatronics, Space Robotics, Sensors and Sensing Systems
Abstract: The unique challenges posed by the space environment, characterized by extreme conditions and limited accessibility, raise the need for robust and reliable techniques to identify and prevent satellite faults. Fault detection methods in the space sector are required to ensure mission success and to protect valuable assets. In this context, this paper proposes an Artificial Intelligence (AI) based fault detection methodology and evaluates its performance on ADAPT (Advanced Diagnostics and Prognostics Testbed), an Electrical Power System (EPS) dataset, crafted in laboratory by NASA.

Our study focuses on the application of a physics-informed (PI) real-valued non-volume preserving (Real NVP) model for fault detection in space systems. The efficacy of this method is systematically compared against other AI approaches such as Gated Recurrent Unit (GRU) and Autoencoder-based techniques.

Results show that our physics-informed approach outperforms existing methods of fault detection, demonstrating its suitability for addressing the unique challenges of satellite EPS sub-system faults. Furthermore, we unveil the competitive advantage of physics-informed loss in AI models to address specific space needs, namely robustness, reliability, and power constraints, crucial for space exploration and satellite missions.

Keywords: Artificial Intelligence in Mechatronics, Mobile Robots, Robot Dynamics and Control
Abstract: Accurate path tracking of wheeled Uncrewed Ground Vehicles (UGVs) in off-road environments faces numerous challenges stemming from the diversity of operational conditions. Traditional model-based controllers for Ackermann-steered vehicles feature good (skid-free) path-tracking performance on flat ground, but performance degrades with increasingly uneven terrain and faster traversal speeds. This paper introduces a novel approach, a Hybrid Deep Reinforcement Learning (HDRL) controller, leveraging the strengths of a Linear Quadratic Regulator (LQR) and a Deep Reinforcement Learning (DRL) controller, for the enhanced path tracking of Ackermann-steered UGVs. The DRL controller primarily compensates for uncertainty in terrain conditions and unknown vehicle parameters but can be computationally expensive to train. The LQR controller guides the DRL controller during the initial training phases, ensuring a more stable performance and achieving higher rewards in early iterations. In doing so, this hybrid methodology offers promise to overcome the limitations of model-based controllers and the sample-inefficient nature of conventional DRL approaches. Preliminary results showcased in the manuscript show promise for the HDRL controller, demonstrating better performance than model-free DRL and conventional feedback controllers.

Keywords: Wed-based Control of Robotic and Automation Systems, Hybrid intelligent systems, Artificial Intelligence in Mechatronics
Abstract: In the logistics field, due to the declining birthrate, aging population, and shrinking workforce, there is growing demand for automation of manual handling tasks. Focusing on robotic picking operations, we developed two grasping methods for various items: rule-based grasp planning that considers the physical characteristics of the items and environment, and DNN-based grasp planning that can learn the grasping points obtained by the same method. Rule-based grasp planning is computationally time-consuming, and DNN-based grasp planning has a lower success rate. Therefore, this paper proposes hybrid-AI grasp planning that integrates these grasp planning methods. We effectively demonstrated that selecting an appropriate grasp planning method by the developed selector can improve throughput because it can combine a high success rate with fast calculation time.

Keywords: Artificial Intelligence in Mechatronics, Neural Networks, Flexible Manipulators and Structures
Abstract: Deep Reinforcement Learning (DRL) combined with demonstration data has made significant strides in formulating manipulation policies. However, the practical collection of ample high-quality demonstrations is time-consuming, and demonstrations generated by humans may not perfectly align with the operational demands of robots. Our study indicates that in manipulation tasks, RL agents are highly sensitive to the quality of demonstrations in both online and offline settings. Consequently, leveraging low-quality or limited demonstrations to assist RL agents in developing superior policies presents a significant challenge.

To address these challenges, we propose an innovative algorithm, TD3+Smooth BC, which modifies TD3fG. In the online setting, this algorithm enables a seamless transition from learning from expert demonstrations to learning from experience, allowing agents to assimilate prior knowledge while mitigating the negative impacts of demonstrations. In the offline setting, TD3+smooth BC dynamically adjusts the weight of maximization of the Q value and imitation to utilize human demonstrations and achieve efficient policy learning effectively. Our algorithm demonstrates notable improvements in the Adroit manipulator and MuJoCo tasks, even with limited demonstrations of mixed failure trajectories.

Keywords: Mobile Robots, Planning and Navigation, Artificial Intelligence in Mechatronics
Abstract: This paper proposes an innovative navigation framework for Autonomous Mobile Robots (AMRs) operating on pedestrian sidewalks. The proposed method breaks down the navigation mission into discrete sidewalk-following tasks between intermediate waypoints, ensuring a seamless journey from start to finish. Two integral modules collaborate to facilitate the entire process. The global sense module (GloS) integrates GNSS (Global Navigation Satellite System), compass, and odometry to plan the path and track the robot’s location. Concurrently, an end-to-end automatic steering module (ASM) leverages a dual-EfficientNetV2 architecture to integrate RGB and depth visions to classify diverse sidewalk scenarios and generate specific local maneuvers to follow the sidewalk and avoid obstacles. Our empirical evaluation demonstrated an accuracy of 98% of the ASM, with a real-time performance on the robot’s embedded system. By deploying the proposed system on our two-wheeled, self-balancing mobile robot for field tests in city streets, the feasibility of employing a geometrical-model-free framework for sidewalk navigation was attested.

Keywords: Artificial Intelligence in Mechatronics, Neural Networks
Abstract: This paper presents three open-source reinforcement learning environments developed on the MuJoCo physics engine with the Franka Emika Panda arm in MuJoCo Menagerie. Three representative tasks, push, slide, and pick-and-place, are implemented through the Gymnasium Robotics API, which inherits from the core of Gymnasium. Both the sparse binary and dense rewards are supported, and the observation space contains the keys of desired and achieved goals to follow the Multi-Goal Reinforcement Learning framework. Three different off-policy algorithms are used to validate the simulation attributes to ensure the fidelity of all tasks, and benchmark results are also given. Each environment and task are defined in a clean way, and the main parameters for modifying the environment are preserved to reflect the main difference. The repository, including all environments, is available at https://github.com/zichunxx/panda_mujoco_gym.

Keywords: Flexible Manipulators and Structures, Modeling and Design of Mechatonic Systems
Abstract: We propose a novel multi-section cable-driven soft robotic arm inspired by octopus tentacles along with a new modeling approach. Each section of the modular manipulator is made of a soft tubing backbone, a soft silicon arm body, and two rigid endcaps, which connect adjacent sections and decouple the actuation cables of different sections. The soft robotic arm is made with casting after the rigid endcaps are 3D-printed, achieving low-cost and convenient fabrication. To capture the nonlinear effect of cables pushing into the soft silicon arm body, which results from the absence of intermediate rigid cable guides for higher compliance, an analytical static model is developed to describe the relationship between the bending curvature and the cable lengths. The proposed model shows superior prediction performance in experiments over that of a baseline model, especially under large bending conditions. Based on the nonlinear static model, a kinematic model of a multi-section arm is further developed and used to derive a motion planning algorithm. Experiments show that the proposed soft arm has high flexibility and a large workspace, and the tracking errors under the algorithm based on the proposed modeling approach are up to 52% smaller than those with the algorithm derived from the baseline model.

Keywords: Modeling and Design of Mechatonic Systems, Design Optimization in Mechatronics, Sensor Integration, Data Fusion
Abstract: This paper introduces an innovative approach to optimize the deployment of a network of multiple frequency modulated continuous wave (FMCW) radars within a designated 3-D space target area. Based on the characteristics of FMCW radar, a novel coverage model is proposed to define the coverage strength of the radar sensor, taking into account essential criteria such as range, field of view, range resolution, field resolution, array factor, and occlusion. This model leads to a quantification of the radar network’s coverage performance, serving as the cost function for sensor network deployment. The Luus-Jaakola (LJ) algorithm is selected to optimize the cost function, renowned for its proficiency in avoiding local optima and enhancing radar deployment task performance. The simulation and experiment results are presented to validate the proposed FMCW radar coverage model and demonstrate the effectiveness of the radar deployment method.

Keywords: Modeling and Design of Mechatonic Systems
Abstract: This work reports a gimbaled-pendulum wave energy converter with a magnetic multi-stable mechanism to better capture multi-directional irregular excitations. To have a deep insight into the multi-stable effect, the dynamic energy conversion is modeled by taking random excitations from multiple directions into account. Moreover, this work investigates the effect of hull swing on the distribution of equilibrium points and potential wells, and analyzes the promotion on energy harvesting performance under different excitations. It is found that the average output power is increased by 6.5% under the sway excitation and by 51.1% under the roll excitation with the help of the multi-stable mechanism. A scalable prototype occupying a space of 0.029 m3 in total is fabricated. Field results under mild sea condition show that the wave energy converter can output electrical power with peak value of 3.83 W and average value of 0.295 W, while the corresponding root mean square amplitudes of the roll and pitch vibrations of the hull are as small as 3.52 degrees and 3.07 degrees. Potential approaches for enlarging the electrical output are also discussed.

Keywords: Modeling and Design of Mechatonic Systems, Micro-Electro-Mechanical Systems, Actuators in Mechatronic Systems
Abstract: Microscale actuation holds transformative potential across various fields by enabling precise and minimally invasive actions, however downsize actuators while keeping relative large actuation range is challenging. Electrohydrodynamics (EHD) forces, arising from electric field-fluid interaction, can greatly deform fluid surface at microscale, yet there is a lack of knowledge regarding the modeling, control, and specificity which hinder their use in microactuator designs. This work, aims to design, model and open-loop control a droplet driven by EHD, focusing on its application in fluid joints (i.e. two solids link together by a liquid droplet) based microactuators. The model merges an energy-based steady-state hysteresis with linear dynamics, using the steady-state inverse as an open-loop controller to control the droplet's height. For a selected design, both steady-state and dynamic models were fitted using a 3μL droplet of glycerin and the control strategy was tested. The model accurately predicts the stable droplet position, while the control strategy maintains a height error under 14 μm, a motion amplitude of 150 μm, and high repeatability. This work contributes to the advancement of microscale actuation by presenting a model and open-loop control strategy for EHD-driven droplets, facilitating practical use as a microactuator for fluid joints in microrobotic applications.

Keywords: Novel Industry Applications of Mechatroinics, Modeling and Design of Mechatonic Systems, Sensors and Sensing Systems
Abstract: To avoid oil leakage accidents in large storage tanks, measurements of metal thicknesses are important to assess the structure conditions. Ultrasonic sensors are widely used to measure metal thicknesses. To realize ultrasonic thickness measurement by robots, it is necessary to realize contact between a probe and surfaces. In this study, we proposed a novel mechanism of a metal thickness measurement module which includes a Scotch Yoke mechanism to convert a robot's movement to a pressing motion of a probe. The proposed module consists of a probe, a slider box, a slider, wheels, and a rotation disk with a pin. When the disk connected to the wheels rotates, the pin moves the slider connected to the probe up and down simultaneously. The module mounted on a magnet-type wall-climbing robot measured the metal thicknesses of the test pieces. We confirmed that the prototype module can realize the contacting and releasing of the probe to surfaces according to the wheel's rotation.

Keywords: Medical Robotics/Mechatronics, Compuational Models and Methods, Modeling and Design of Mechatonic Systems
Abstract: The profile estimation for continuum robots is a crucial problem concerning automatically controlling robots. The conventional method is based on the Cosserat rod theory, which is limited by the dependence of the convergence on the initial guess and computational complexity. To tackle these issues, this paper proposes a general kinetostatic model to estimate the profile of the tendon-driven continuum robot (TDCR). We first abstract the backbone of the TDCR as an Euler-Bernoulli beam and then derive the spatial beam constraint model of a circular cross-section beam without considering torsion and shear. Next, taking a single-section TDCR as an example, we provide comprehensive modeling, considering the driving tendon tensions, friction, gravity, and external forces. Subsequently, an algorithm based on the chained spatial beam constraint model is proposed to estimate the robot's profile. The method can be generalized to the TDCR with different configurations. Simulations demonstrate the accuracy, computational efficiency, and computational success rate of our method, as well as its advantages over the state-of-the-art. Real-world experiments have also been performed to validate the effectiveness of our method with three different configurations of the TDCR.

Keywords: Control Application in Mechatronics, Actuators in Mechatronic Systems, Actuators
Abstract: In recent years, the demand for collaborative robots has been increasing. As collaborative robots must be safe against contact. The purpose of this research was to develop robots that can perform tasks involving contact in collaboration with humans. A torque sensor is generally used to detect the external force at contact, but can reduce the rigidity of the robot. Thus, in this paper, we propose impedance control without a torque sensor for an actuator comprising a motor and reduction gear. Position-control-based impedance control was applied to the proposed method, and the torque can be estimated without a torque sensor using a highly efficient reduction gear. In addition, an external-force feedback gain is introduced for position-control-based impedance control and an external contact force reduction method is realized based on the angular transmission error of the reduction gear. From experiments, the proposed method achieved both position control and force control. As a result, the external contact force was reduced by approximately 10%.

Keywords: Control Application in Mechatronics, Design Optimization in Mechatronics, Medical Robotics/Mechatronics
Abstract: This paper presents the concept, implementation, feedback control, and experimental verification of a noncontact magnetic manipulator that relies on a controllable array of permanent magnets to manipulate magnetized objects inside a workspace encircled by the magnets. To gain control over the aggregate magnetic field inside the workspace, the position of each magnet is independently controlled by a linear servomotor that dynamically changes the distance between that magnet and the workspace. By feedback control of the array of servomotors, the magnetic force applied to a magnetized object inside the workspace is dynamically adjusted to steer it along a desired reference trajectory. The successful steering of a small magnetic bead is demonstrated by experiments performed on a planar magnetic manipulator, designed and prototyped with six linear servomotors and six permanent magnets.

Keywords: Space Robotics, Flexible Manipulators and Structures, Control Application in Mechatronics
Abstract: In the space habitation program for lunar exploration, it is quite difficult to design and manufacture materials locally. Therefore, the basic approach is to fabricate the materials on Earth, store them in rockets, and deploy and install them on the Moon. The habitation facility must be as compact as possible and have a mechanism with excellent deplorability and storability. The authors have focused on the Ishimatsu fold structure, which features the 3-dimensional folding of thick, rigid columnar structure. When unfolded, the cross section of this structure becomes hexagonal, and 6 surfaces composed by the same mechanism unfold simultaneously to form a prismatic columnar shape with complex shape changes. In this study, we investigated the usefulness of the Ishimatsu fold structure by dividing and expanding each module of the structure. Since each module and actuator can be stored small, they can be reconfigured to create various shapes. In this paper, we analyze the motion and dynamics of the expanded deployable structure, and investigate the power and effective placement of the actuators to enable deployment.

Keywords: Control Application in Mechatronics, Modeling and Design of Mechatonic Systems, Medical Robotics/Mechatronics
Abstract: Maintaining introaocular pressure stability is critical to surgical effectiveness and safety in intraocular surgery. In cataract lens removal procedure, the continuous fluid irrigation and aspiration creates disturbances in the intraocular pressure, which subsequently causes deformation and damage to intraocular tissues. Incidental surge phenomena, when materials blocking the aspiration pathway are suddenly released, creating sudden pressure drop and cornea collapse. To improve the pressure stability under such severe pressure disturbances, this paper presents an add-on irrigation and pressure control system to existing fluid control machine. The effect of the enhanced dynamic response for the closed loop pressure control is demonstrated by reduced corneal deformation in pig eye experiment.

Keywords: Motion Vibration and Noise Control, Control Application in Mechatronics
Abstract: In this paper, a model-matching input shaping controller will be designed for a double-pendulum overhead crane with time-varying cable length. It will be demonstrated that the propagation of vibration suppression allows us to eliminate oscillations for both pendulums, even though only one reference model is permitted. Comparative simulation results are presented to highlight the advantage of the proposed approach over the standard input shaping controller. An experimental study is also conducted on an actual crane.

Keywords: Control Application in Mechatronics, Learning and Neural Control in Mechatronics, Mobile Robots
Abstract: Challenges in trajectory generation in robotics such as nonlinearities, non-convex constraints, many optimization variables and redundancy lead to new developments in the use of data-based methods. In this paper, a combination of a data- and model-based approach for trajectory generation for a redundant mobile manipulator with 10 degrees of freedom is presented with the goal of reducing the computational cost and improving scalability. A computationally efficient neural network regression model is proposed which predicts the joint trajectories generated from an optimal control problem considering the system equations, redundancy, singularities, nonlinear kinematic and dynamic constraints as well as collisions. The prediction is then improved through a subsequent quadratic programming with low computational cost, ensuring the compliance with the system equations and increasing the tool-center-point target reaching accuracy.

Keywords: Machine Vision, Micro/Nano Manipulation, Sensors and Sensing Systems
Abstract: To achieve an observation stage with 6 degrees of freedom, a specimen was placed at the center of a transparent sphere or polyhedron. This novel configuration enables not only positional tracking, but also posture tracking, as well as scanning on three rotational axes. After discussing the solution space for spherical and polyhedral shapes and the mechanisms available to achieve 6-DoF, we demonstrate our invention with two proof-of-concept prototypes: (1) the polyhedron-gimbal, which allows simultaneous rotation of pitch, yaw, and roll, and (2) an actuated sphere-retractable axis version, which uses friction for pitch and roll, and a gear mechanism for yaw. To the best of our knowledge, this is the first example of omni-directional imaging suitable for 3D stereomicroscopy of biological organisms. In the future, it will be applied to the monitoring of 3D cellular growth in various conditions. Video abstract: https://youtu.be/kJLVPvKqaOc

Keywords: Machine Vision, Image Processing, Software Design for System Integration
Abstract: This paper presents a novel integration approach to enable EtherCAT-bus connection for commercial depth cameras. Thereby, a microcontroller-based EtherCAT slave is designed which controls the data transmission from the depth camera onto the fieldbus. As a demonstration case, a human-robot collaboration application is designed, where the proposed camera module monitors a five-axis robotic arm, thus ensuring safety through timely obstacle detection, and execution of safety stops. Achieving data transmission rates exceeding 25Mbit/s and detection times under 25ms, the implemented system outperforms existing technologies in human-robot collaboration, which allows to reduce the minimal safety distance to 75mm.

Keywords: Machine Vision, Image Processing, Part Feeding and Object Handling 
Abstract: Autonomous and semi-autonomous robot manipulation systems require fast classification and localization of objects in the world to realize online generation of motion plans and manipulation waypoints in real-time. Furthermore, constraints and estimated plausible motions of objects of interest in space is paramount for autonomous manipulation tasks. For non-grasping tasks like pushing a box or opening an unlatched door, physical properties such as the center of mass and location of constraints like hinges or bearings must be considered. This paper presents a methodology for rapidly inferring constraints and motion plans for objects of interest to be manipulated. This approach is based on a combination of object detection, instance segmentation, localization methods, and algebraically relating different semantically labeled objects. These methods for motion estimation are implemented on a color-depth camera (RGB-D) and a 7 degree-of-freedom serial robot arm. The algorithm's performance is evaluated through different arm poses, assessing both centroid accuracy and estimation speed, and motion estimation performance. Algorithms are tested on an exemplar problem consisting of a block constrained on a dual linear rail system, i.e., constrained linear motion. Experimental results showcase the scalability of this approach to multiple classes with sublinear slowdowns and linear motion plan direction errors as low as 1.23E-4 [rad]. The manuscript also outlines how these methods for rapid constrained object motion estimation can be leveraged for other applications.

Keywords: Machine Vision, Neural Networks
Abstract: In this paper, a novel method for monocular estimation of connector orientation in wire and cable harnesses is introduced. The proposed approach combines Deformable Linear Objects (DLOs) priors with a learning-based technique for smooth angle classification, enabling precise prediction of connector orientation using only a single RGB image. The integration of DLO perception is crucial in recovering an initial coarse understanding of the connector pose. This is accomplished by linearly projecting the identified DLO endpoint using the predicted spline-based DLO representation model. To estimate the axial orientation of the connector, the proposed approach incorporates a smooth labeling technique in the angle classification process. This ensures effective handling of the circular nature inherent in angular data. Additionally, a self-supervised acquisition and annotation of the dataset samples is employed. To assess the effectiveness of the proposed method, we conducted experiments with a collection of real-world connectors sourced from the automotive sector. The outcomes underscore the potential applications of the proposed method in tasks related to the robotic manufacturing and assembly of complex deformable linear objects, such as wire harnesses.

Keywords: Planning and Navigation, Machine Vision, Control Application in Mechatronics
Abstract: The green chile crop is entirely hand-harvested in New Mexico while the growing labor shortage has caused a significant reduction in production. This work presents the robotic harvesting of chile peppers in a lab setting, employing a 6-DOF robotic arm with a scissor-type cutting end-effector. The system utilizes a machine learning-based computer vision and a depth camera to detect and localize chile peppers in the camera frame. The locations are then transformed into the robot's operational frame. A motion planning algorithm was developed to minimize the robot's travel time for harvesting. A correction equation is derived to address inaccuracies in camera-based localization while eliminating chiles that are not reachable for the robot. From a dataset of 86 chile peppers, the study reports key harvesting metrics: a detection success rate of 62.8%, a localization success rate of 90.74%, a detachment success rate of 55.10%, a harvest success rate of 31.39%, and a damage rate of 6.97%.

Keywords: Control Application in Mechatronics, Actuators in Mechatronic Systems, Motion Vibration and Noise Control
Abstract: Repetitive motion is an important operation in manufacturing processes and other applications. It is thus necessary to design control systems that can track repetitive-motion reference signals for dual-input-single-output (DISO) systems. This paper proposes a control scheme to realize precise repetitive motion in DISO systems. The proposed design method utilizes adaptive feed-forward cancellation (AFC) to compensate the position error signal for the reference signal. This approach contributes to improving DISO system control performance. In addition, the control system can eliminate the negative impact due to the waterbed effect. The proposed control system was implemented in an experimental system, and the experimental results indicate the effectiveness of the proposed method.

Keywords: Data Storage Systems, Motion Vibration and Noise Control, Control Application in Mechatronics
Abstract: In this paper, we present a loop-shaping method that incorporates unstable poles for the magnetic-head positioning system in a hard disk drive (HDD). The proposed method involves introducing unstable poles instead of the conventional stable poles for the resonance filter used in loop shaping. In our approach, the resonant filter is designed to realize a circle that includes the coordinate [-1, 0j] on the Nyquist plot of the open-loop characteristics in the control system. Validation results using the HDD benchmark problem demonstrate that our proposed methods effectively reject disturbances in the high-frequency range while maintaining robust performance.

Keywords: Identification and Estimation in Mechatronics, Control Application in Mechatronics
Abstract: Estimation of an accurate frequency response function (FRF) of a target system is crucial to design fine servo controllers that realize fast and precise positioning control. The empirical transfer function estimation (ETFE) is the most representative and simplest FRF estimation method in terms of industrial utility. However, its applicability is limited to input and output signals of a target system measured during periodic or reciprocating operations, due to leakage errors induced by the discrete Fourier transform. Recently, an FRF estimation method combining ETFE with differential filtering has been proposed, which enables accurate FRF estimation in point-to-point motion. This paper theoretically clarifies the relationship between leakage-free condition and the differential filtering order in the ETFE-based FRF estimation framework. Furthermore, it is demonstrated through simulations that increasing the differential filtering order can broaden the input and output signals acquisition conditions that enables accurate FRF estimation.

Keywords: Actuators, Actuators in Mechatronic Systems
Abstract: In a conventional scanner with an electromagnetic actuator for high-speed scanning motions with nanometer resolution, its motor constant needs to be determined in a tradeoff between the achievable speed and the motion precision due to noise from the inputs. To overcome the tradeoff, this paper proposes a scanner that integrates a pair of reluctance actuators for a tunable motor constant. Model-based analysis shows that the motor constant can be tuned by introducing a bias current, and the motion precision can be improved by decreasing the motor constant when a high force is unnecessary. To demonstrate the effectiveness, a laboratory setup is developed with motion control, achieving a high control bandwidth of about 300 Hz. Experimental results show that the motor constant of the proposed scanner can be decreased by a factor of 9, improving the positioning error from 16.7nm to 5.2 nm at a static point. The results successfully demonstrate the tuning function of the proposed scanner and its effectiveness on the motion precision.

Keywords: Motion Vibration and Noise Control, Control Application in Mechatronics, Modeling and Design of Mechatonic Systems
Abstract: This paper presents the design, implementation and evaluation of a vibration isolation system with a magnetically levitated platform and tunable zero-power gravity compensation. The system, motivated by the stringent requirements of high-precision applications, employs Lorentz actuators for the platform’s six degrees of freedom. Zero-power gravity compensation is achieved by electropermanent magnets, allowing adaptation to a varying payload while maintaining a constant operating point. Using decoupling transformations, the platform is stabilized by decentralized position control. For vibration isolation in the vertical direction, the position control bandwidth is reduced to 8 Hz by compensating the negative stiffness of the electropermanent magnets, resulting in an attenuation of floor vibrations with −40 dB/decade above this frequency. Acceleration feedback further reduces the transmissibility by 9.7 dB (67 %). The tunable gravity compensation supports a total load of 6.34 kg and reduces the power consumption of the Lorentz actuators by 98.9 %.

Keywords: Motion Vibration and Noise Control, Sensor Integration, Data Fusion, Sensors and Sensing Systems
Abstract: Estimating velocity and acceleration from an encoder requires high accuracy and wide bandwidth in motion control. This study aims to estimate velocity and acceleration by explicitly considering the quantization process of the encoder. This paper proposes a quantization step aware convex optimization method that makes it numerically easier to solve. Its solution can be accelerated by applying the proposed initial value. The developed approach improves the estimation accuracy from the encoder's sequential outputs. The improvement of the accuracy and the possibility of its real-time use are validated by the implementation on FPGA.

Keywords: Modeling and Design of Mechatonic Systems, Tele-operation, Medical Robotics/Mechatronics
Abstract: Surgical robotic systems equipped with micro-scale, high-dexterity manipulators have shown promising results in minimally invasive surgery (MIS). One barrier to the widespread adoption of such systems is the prohibitive cost of research and development efforts using current state-of-the-art equipment. To address this challenge, this paper proposes a low-cost and modifiable tendon-driven continuum manipulator for MIS applications. The device is capable of being teleoperated in conjunction with a macro-scale six-axis robotic arm using a haptic stylus. Its control software incorporates and extends freely available and open-source software packages. For verification, we perform teleoperation trials on the proposed continuum manipulator using an electromagnetic tracker. We then integrate the manipulator with a UR5e robotic arm. A series of simulated tumour biopsies were conducted using the integrated robotic system and an anatomical model (phantom), validating its potential efficacy in MIS applications. The complete source code, CAD files for all additively manufactured components, a parts list for the manipulator, and a demonstration video of the proposed system are made available in this work.

Keywords: Medical Robotics/Mechatronics, Design Optimization in Mechatronics, Modeling and Design of Mechatonic Systems
Abstract: The manipulation difficulties in laparoscopic procedures inspire the development of surgical robotic systems. To perform tissue dissection and coagulation, electrosurgical instruments and ultrasonic scalpels are integrated. Ultrasonic scalpels, which utilize high-frequency vibration generated by ultrasonic transducer to dissect and coagulate tissues, are safer than electrosurgical instruments due to concentrated energy release. However, the rigid straight waveguides involved in conventional ultrasonic scalpels prevent their integration into single-port surgical robot, within which multi-joint articulated or continuum bendable instruments are used. Putting miniature transducer at the distal end of the instruments is a potential way to integrate ultrasonic scalpel. However, the existing miniature ultrasonic transducers arranged at instrument distal ends have limited energy efficiency due to their 55.5-kHz half-wavelength design. This paper hence proposes the design of a 120-kHz full-wavelength miniature ultrasonic transducer with a diameter of only 6 mm. The proposed 120-kHz full-wavelength structure can provide sufficient energy efficiency while maintaining the transducer’s compact size. Finite-element model is utilized to optimize the proposed transducer’s structure. Tissue dissection capability of the proposed 120-kHz miniature ultrasonic scalpel is demonstrated experimentally. It’s promising for the proposed design to be integrated into an 8 mm continuum instrument for single-port robotic surgery.

Keywords: Parallel Mechanisms, Rehabilitation Robots, Medical Robotics/Mechatronics
Abstract: Cervical traction is a common and effective treatment for degenerative disk diseases and pain in the cervical spine. However, the manual and mechanical methods of applying traction to the head-neck are limited due to variability in the applied forces and orientation of the head-neck relative to the shoulder during the procedure. Current robotic neck braces are not designed to apply independent vertical translation, or traction, to the brace end-effector connected to the head, making them unsuitable for traction application. This work proposes a novel architecture of a robotic neck brace, which can provide vertical traction to the head while keeping the head in a prescribed orientation, with flexion and lateral bending angles. In this paper, the kinematics of the end-effector attached to the head relative to a coordinate frame on the shoulders are described as well as the velocity kinematics and force control. The paper also describes benchtop experiments designed to validate the position control and the ability of the brace to provide a vertical traction force. It was shown that the maximum achievable end-effector orientations are 16◦ in flexion, 13.9◦ in extension, and ±6.5◦ in lateral bending. The kinematic model of the active brace was validated with maximum root mean square error of 2.41◦ using an independent motion capture system. In three different orientations of the end-effector, neutral, flexed, and laterally bent, the brace was able to provide a consistent upward traction force during intermittent force application. The level of force variability in these configurations outperforms manual traction with standard deviations in the force error of 0.55, 0.29, and 0.07N, respectively. This work validates the mechanism's ability to achieve a range of head orientations and provide consistent upward traction force in these orientations, making it a promising intervention tool in cases of cervical disk degeneration.

Keywords: Medical Robotics/Mechatronics
Abstract: This paper provides a preliminary experimental assessment of a flexible endoscope driven by antagonistic twisted string actuation (TSA). Traditional endoscope designs have relied on manual manipulation or actuation systems lacking force control loops, limiting their versatility and ease of use. The proposed approach leverages the benefits of additive manufacturing to create customizable, deformable endoscope’s tip structures, while TSA provides an efficient and potentially compact actuation mechanism. The experimental evaluation encompasses two key aspects of endoscope performance: tissue interaction and stiffness variation. Through a series of controlled experiments, the endoscope’s ability to interact with mock biological tissues is assessed, demonstrating successful force application using both agonist-only and antagonistic functioning modalities. Furthermore, the endoscope’s resilience to external disturbances is evaluated, with results showing significant improvements in stiffness and response to perturbations when utilizing antagonistic control. These findings highlight the potential of the proposed device to improve flexible endoscopy design and functionality. By integrating advanced manufacturing techniques with innovative actuation mechanisms, robotic flexible endoscopes can offer enhanced maneuverability, diagnostic precision, and patient safety.

Keywords: Control Application in Mechatronics, Medical Robotics/Mechatronics, Identification and Estimation in Mechatronics
Abstract: To systematically evaluate mechanical ventilators and their automation concepts, test lungs can be used in hardware-in-the-loop (HiL) simulations. However, most test lungs do not simulate lungs with spontaneous breathing. This study presents a mechatronic test lung that consists of a bellow and a voice coil actuator. After modeling and parameter estimation, the model was used for the synthesis of a robust controller. The whole system was validated with a reference lung model and recorded measurement data of volume flow. The model identification resulted in a root-mean-square error (RMSE) of 0.96 mm. The controller achieved a maximum RMSE of 0.062 liters per second and a relative compliance error of 5.88 %. The test lung has the potential to enable HiL simulations of mechanical ventilation with spontaneous breathing.

Keywords: Neural Networks, Artificial Intelligence in Mechatronics, Medical Robotics/Mechatronics
Abstract: In this manuscript, we present a sophisticated robotic system integrated with an adaptive optimization algorithm specifically designed for Brachytherapy in the treatment of prostate cancer. The principal novelty of this system lies in the algorithm itself, which is crafted to dynamically modify needle trajectories based on the real-time movements of the prostate gland during the local intervention.

By utilizing real-time positional data derived from Magnetic Resonance Imaging (MRI), the algorithm guarantees accurate targeting of the prostate by adjusting to its continual motion and deformation. This level of precision holds significant importance in Brachytherapy, as the precise emplacement of radioactive seeds directly influences the effectiveness of the treatment and minimizes harm to surrounding healthy tissues.

Our findings reveal a substantial enhancement in the precision of radiation seed placement, directly linked to a more efficient delivery of radiation. Moreover, the adaptive characteristics of the algorithm notably diminish the quantity of needle insertions, resulting in a less intrusive treatment process for patients. This decrease in needle insertions also contributes to a reduced risk of infections and shorter recovery periods.This innovative robotic system, bolstered by the adaptive optimization algorithm, enhances the coverage of targets achieved compared to a conventional combinatorial method by approximately 12% with a reduced need for needles.

Keywords: Modeling and Design of Mechatonic Systems, Biomechatronics, Legged Robots
Abstract: Robotic exploration in natural environments requires adaptable, resilient, and stable interactions with uncertain terrains. Most state-of-the-art legged robots utilize flat or ball feet that lack adaptability and are prone to slip due to point contact with the ground. In this paper, we present guidelines to design an adaptive foot that can interact with the terrain to achieve a stable configuration. The foot is inspired by goat hoof anatomy that incorporates roll and yaw rotations in Fetlock and Pastern joints, respectively. To ensure adaptability with stability in physical interaction and to prevent the foot from collapsing, we provide a lower bound on each joint's stiffness. Additionally, we also render an upper bound to conform to the high force exchange during interactions with the ground consisting of certain roughness. Based on these guidelines, we design the hoof and experimentally validate the theoretical results with a loading test setup in lab settings. We use four different friction materials with various triangular, rectangular, and semi-circular extrusions to simulate common ground features. We observe that hooved pads require more load for the system to be unstable. Any anatomical-inspired foot can be designed based on the guidelines proved analytically and experimentally in this article.

Keywords: Legged Robots, Robot Dynamics and Control, Control Application in Mechatronics
Abstract: This paper introduces a loco-manipulation strategy for a quadruped robot operating on deformable terrains. A complete spatial robot model is built as the controlled system. Linear and nonlinear spring-damper models are adopted to represent the terrain deformation. The Operational Space Formulation (OSF) is employed to map the configuration space dynamics to task space dynamics. The Model Predictive Control (MPC) methodology is studied and implemented to direct the controlled system. The operational space motion equations and their interaction with deformable terrain are used as the fundamental model for the MPC framework. A force control strategy is employed on the legs to counteract gravitational effects and stabilize the body on deformable terrain, while a motion control strategy is applied to the arm for the object-manipulating task. The simulation results demonstrate that the proposed controller is feasible for these applications.

Keywords: Legged Robots, Mobile Robots
Abstract: This paper presents a novel robot called Orimo that combines the advantages of transformable wheels and modular robots. In addition to enhancing its own mobility, the robot can collaborate with modules to accomplish more complex tasks. The design of the robot utilizes origami mechanisms and printed circuit boards, offering characteristics of low cost and rapid manufacturing, meeting the requirements of extensive usage and quick replacement. The design of the robot in this paper demonstrates good single-module mobility. Through the transformation mechanism, it is able to climb an obstacle whose height is up to 1.6 times its wheel radius, effectively passing through complex terrains. Furthermore, the robot can use module collaboration for assembly, catering to a variety of work requirements and providing a variety of problem-solving strategies.

Keywords: Legged Robots, Robot Dynamics and Control, Biomechatronics
Abstract: This research concentrates on enhancing the navigational capabilities of Northeastern University's Husky, a multi-modal quadrupedal robot, that can integrate posture manipulation and thrust vectoring, to traverse through narrow pathways such as walking over pipes and slacklining. The Husky is outfitted with thrusters designed to stabilize its body during dynamic walking over these narrow paths. The project involves modeling the robot using the HROM (Husky Reduced-Order Model) and developing an optimal control framework. This framework is based on polynomial approximation of the HROM and a collocation approach to derive optimal thruster commands necessary for achieving dynamic walking on narrow paths. The effectiveness of the modeling and control design approach is validated through simulations conducted using Matlab.

Keywords: Legged Robots
Abstract: This paper outlines a testing of quadruped robot mobile manipulation using robotic arm in oil and gas facilities to explore the opportunities and challenges of a full unmanned operation. Robotic arm replicates the agility of human hand, wrist, and fingers with an ability to perform hazardous tasks in inaccessible area. Four manipulation activities of panel door opening, valve opening, buttons and switches on/off and liquid sample collection are performed. A mission workflow for the arm manipulation performance is identified and each task is evaluated in term of accuracy, time to completion, and precision.

Keywords: Legged Robots, Walking Machines, Design Optimization in Mechatronics
Abstract: Quadruped robots are used for a wide variety of transportation and exploration tasks due to their high dexterity. Currently, many studies utilize soft robotic legs to replace rigid-link-based legs, with the aim to improve quadruped robots' adaptability to complex environments. However, the conventional soft legs still face the challenge of limited load-bearing capacity. To cope with this issue, we propose in this work a type of soft-rigid hybrid leg, which is synthesized by using a multi-stage topology optimization method. A simplified model is also created to describe the kinematics of the synthesized soft leg. Using the realized legs, we have developed a turtle-inspired quadruped robot called TurBot. By mimicking the walking pattern of a turtle, two motion gaits (straight-line walking and turning) are designed to realize the robotic locomotion. Experiments are also conducted to evaluate the walking performance of TurBot. Results show that the realized robot can achieve stable straight-line walking and turning motions. In addition, TurBot can carry up to 500g extra weight while walking, which is 126% of its own body weight. Moreover, different locomotion tests have also successfully verified TurBot's ability to adapt to complex environments.

Keywords: Actuators in Mechatronic Systems, Control Application in Mechatronics, Humanoid Robots
Abstract: This paper proposes a method for controlling force and position in a synchronous direct-drive electrostatic linear motor. Using a spring-like behavior of synchronous motors, the proposed controller regulates the contact force in a manner similar to that of series elastic actuators. Discussions regarding similarities and differences between series elastic actuators and the proposed method imply that their dynamic behaviors are different. The proposed controller consists of a force control part and a position control part, one of which is automatically selected based on the operating conditions. The position and force controllers each independently command the velocity based on the position or force error. The lower of the two velocities is selected, allowing a smooth automatic transition between the two control modes. Based on the selected velocity, the driving signal is calculated under the assumption of synchronous operation and fed to the actuator. The proposed control method is simulated and experiments are performed using prototype electrostatic linear motors. The experimental results confirm the smooth transition between the position and force control modes, as well as the good controllability of the contact force.

Keywords: Actuators, Rehabilitation Robots, Actuators in Mechatronic Systems
Abstract: The operation of electric actuators across a wide temperature spectrum poses a formidable challenge in maintaining actuator homeostasis—the ability to generate a consistent response for a given input. This challenge arises mainly due to torque constant variations resulting from changes in magnetic flux density with temperature fluctuations. This study introduces a novel method to predict and compensate for these variations by developing a thermal model for the actuator, which allows for real-time estimation of the temperature of the inaccessible rotating magnet for effective compensation. The research seeks to advance actuator homeostasis beyond conventional methods that rely solely on the temperature of static components such as the stator or housing. The effectiveness of the proposed algorithm is verified through comparison with the conventional open-loop torque control algorithm. Additionally, the stability of the closed-loop system, focusing on temperature convergence with the proposed algorithm, is analyzed. This methodology suggests a promising path for developing drive systems that maintain actuator homeostasis in diverse conditions, addressing the root causes of system variability.

Keywords: Actuators in Mechatronic Systems, Design Optimization in Mechatronics, Flexible Manipulators and Structures
Abstract: In recent years, cable-driven continuum robots have emerged as a notable focus in robotic research. Achieving a stable and precise controller for such robots requires careful consideration of measuring cable tension force. This paper introduces an innovative design and optimization approach using strain gauges to create a cable tension force sensor (CTFS) that is stable, low-noise, and cost-effective. The methodology involves finite element method (FEM) analysis and optimization to determine the optimal sensor structure based on design requirements. The CTFS design structure is fabricated with 3 types of strain gauges arrangement to conduct the generality. Signal processing circuits for the sensor are developed to handle signals from the CTFS strain gauge bridge. Additionally, the study details the fabrication of three types of CTFS modules to comprehensively assess the proposed designs. Experimental validations, including calibration and temperature sensitivity, are conducted to verify the CTFS in various aspects. The experimental results of the cable tension force sensor shows that the CTFSs can provide high sensitivity with 0.31mV/N, 0.37586mV/N and 0.3197mV/N along with high stability for CTFS-Type1, CTFS-Type2 and CTFS-Type3 respectively. Finally, the application validation demonstrates the potential effectiveness of the cable tension force sensor for affordable, custom continuum robot actuators.

Keywords: Actuators in Mechatronic Systems, Flexible Manipulators and Structures, Modeling and Design of Mechatonic Systems
Abstract: Pipe inspection robots are critical for detecting leaks or cracks, especially in environments that are harmful or inaccessible to humans. In particular, sewage pipes pose significant challenges for traditional rigid pipe robots because they can be filled with obstacles and liquid. Soft robots have been proposed to address some of the issues, but they are still limited in their ability to negotiate obstacles. In this paper, we propose a novel pipe inspection robot powered by a new class of bistable inflatable fabric actuators (BIFA). The entire robot weighs only 350 grams and can exert around 35 N of force by firmly anchoring to the pipe. It is also able to operate in pipes that are blocked by up to 34%. To understand the dynamics of the robot and simulate it for gait optimization, a reduced-order model is proposed and calibrated with characterization experiments including static loading, step response, and anchor test. A Central Pattern Generator (CPG) is also employed to parameterize the gait, enabling Bayesian Optimization in simulation to maximize the robot’s speed inside an unobstructed pipe. The optimized gait from the optimization is directly deployable on the real robot and results in a 120% speed increase over the baseline at 23 mm/s, showing the effectiveness of our model and the importance of gait selection for pipe robots.

Keywords: Actuators in Mechatronic Systems, Rapid Prototyping, Actuators
Abstract: Multi-material additive manufacturing that combines electrically conductive materials with thermally conductive, but electrically insulating, materials presents new opportunities for creating novel and complex electromagnetic actuators. While conductive inks have previously been used to print a wide range of circuits, sensors, and antennas, little effort has been made to additively manufacture >1 A, multi-layer, and multi-coil actuators such as rotary electric motors. In this work, we design, manufacture, and characterize a novel, fully 3D-printed, multi-layer three-phase electromagnetic stator for an axial flux rotary motor. The stator consists of fourteen layers of six coils composed of silver nanoparticle ink deposited using direct-write printing onto electrically insulating and thermally conductive copper-filled polylactic acid filament deposited using fused deposition modeling. To demonstrate this concept, we first outline the material selection, stator design, and printing process. Then, models for the thermal characteristics and output motor torque are developed and compared with experimental results. Measurements indicate that the 3D-printed dual-rotor axial flux motor produces 1.5 Nmm/A of torque without gearing, has a maximum 7.6% power conversion efficiency, and can operate continuously at up to 125°C at 14.0 W (4.0 A) input power. To demonstrate the capabilities of a fully 3D-printed axial flux motor, a 3D-printed fan, gripper, and wheeled vehicle are demonstrated. With the ability to rapidly prototype low-cost, complex electric motor stators, new geometries for electric rotary actuators can be explored including fully-embedded and print-in-place concepts.

Keywords: Actuators in Mechatronic Systems, Legged Robots, Actuators
Abstract: The usage of parallel elastic actuators (PEA) in legged robots could potentially enhance the joints and increase energy efficiency by providing extra torques. However, the current design that adopts tension springs or spiral springs usually requires additional working space for PEA add-ons and enlarges size and mass too much. Besides, they often tune the spring parameters especially the spring constant by hand, failing to achieve optimal performance when considering multiple objectives. To tackle these issues, this paper designs a compact dual-slide PEA (DS-PEA) leg that adopts a compression spring structure. Through integrating with a dual-slide mechanism, the PEA elements are attached tightly to the transmission, resulting in a small-size and light-weighted design. Furthermore, we adopt a multi-objective optimization method, i,e, multi Pareto fronts quantify, to automatically choose the proper spring constant. Simulation and hardware experiments demonstrate that peak torque, motor power, and cost of transport for motion tracking are all largely reduced, even when working at multiple trajectories. Extensive hopping experiments further validate the dynamic motion capability and the energy efficiency of the delicate design. The compact DS-PEA leg will be used in a quadruped robot shortly.

Keywords: Identification and Estimation in Mechatronics, Artificial Intelligence in Mechatronics, Machine Learning
Abstract: As human-robot interaction (HRI) advances, the nuanced interpretation of implicit commands embedded in human gestures becomes paramount for fostering seamless collaboration. In this context, we present a novel machine learning algorithm designed to endow robots with the ability to decipher implicit commands from Inertial Measurement Unit (IMU) sensor data worn at specific locations on the human body. Our approach integrates memory and attention mechanisms inspired by ideomotor cues, allowing the robot to comprehend both temporal and spatial relationships within the sensor data. The attention mechanism operates bidirec- tionally, enhancing the system’s awareness of the temporal sequence of human movements and the spatial interdepen- dencies between sensor data across different body locations. This unique spatial attention enables the robot to understand the kinematic chain between joints during human motion, accommodating variations in sensor data arising from factors such as height differences and motion range capacity. Drawing on prior research in attention mechanisms, ideomotor cues, and memory augmentation, our algorithm represents a significant advancement in addressing the challenges of implicit command understanding in HRI. The proposed system’s adaptability and nuanced comprehension of human gestures make it well- suited for diverse anatomies and movement patterns. Through comprehensive experiments, we demonstrate the effectiveness of our algorithm, paving the way for more intuitive and adaptable robotic systems in real-world applications.

Keywords: Genetic Algorithms, Artificial Intelligence in Mechatronics, Sensor Integration, Data Fusion
Abstract: This work presents a genetic algorithm to evaluate a suitable path for robotic manipulation of elastic objects. The goal is to find a path, given an initial and final position, that accounts for the distance covered by the robot while minimising the forces perceived. These forces are generated by flexible objects that are difficult to model analytically. The proposed model-free approach considers these elastic forces in the fitness functions, making the genetic algorithm stiffness-aware. Furthermore, a dynamic exploration strategy allows for the convergence to effective solutions in a finite number of iterations. A simulated analysis of the suitable parameter configuration is performed for the robotic platform employed in the experiments. These parameters are then used in the validation of the method, demonstrating positive outcomes of the proposed approach in terms of convergence and effectiveness.

Keywords: Identification and Estimation in Mechatronics, Artificial Intelligence in Mechatronics, Modeling and Design of Mechatonic Systems
Abstract: In the research and application of robotic manipulator systems, the friction phenomenon poses challenges to system stability and control precision. To further improve the parameter identification accuracy in traditional friction modeling for robotic manipulators, this paper proposes a friction model parameter identification method based on the Physics Informed Neural Network (PINN). The proposed method takes the relative velocity and normal pressure in the motion of the robotic manipulators as the information input items, with the friction and model parameters as outputs. The network parameters and identification parameters are updated according to the Adam method, achieving a more precise identification of friction parameters. It comprehensively considers friction mechanism information and data information to jointly construct the objective optimization function. Through simulation comparisons with noisy/noise-free data, the PINN method is validated to have higher identification accuracy than Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), with an average reduction of 30% and 50% in the identification error rates for noise-free and noisy data, respectively.

Keywords: Modeling and Design of Mechatonic Systems, Artificial Intelligence in Mechatronics, Fuel Cells and Alternative Power Sources
Abstract: This study explores the use of an emotional based controller for transient stability and voltage regulation in a power system. The design of the controller draws inspiration from the emotional reactions observed in the human brain. The performance of the closed-loop controller is evaluated under both standard and faulty power system conditions. The robustness of the proposed controller is demonstrated through hardware-in-the-loop implementation and MATLAB/Simulink simulations. The findings confirm the superior performance of the controller under consideration.

Keywords: Artificial Intelligence in Mechatronics, Neural Networks, Machine Learning
Abstract: This project introduces a framework to enable robots to recognize human hand signals, a reliable and feasible device-free means of communication in many noisy environments such as construction sites and airport ramps, to facilitate efficient human-robot collaboration. Various hand signal systems are accepted in many small groups for specific purposes, such as Marshalling on airport ramps and construction site crane operations. Robots must be robust to unpredictable conditions, including various backgrounds and human appearances, an extreme challenge imposed by open environments. To address these challenges, we propose Instant Hand Signal Recognition (IHSR), a learning-based framework with world knowledge of human gestures embedded, for robots to learn novel hand signals in a few samples. It also offers robust zero-shot generalization to recognize learned signals in novel scenarios. Extensive experiments show that our IHSR can learn a novel hand signal in only 50 samples, which is 30+ times more efficient than the state-of-the-art method. It also demonstrates a robust zero-shot generalization for deploying a learned model in unseen environments to recognize hand signals from unseen human users.

Keywords: Artificial Intelligence in Mechatronics, Machine Learning, Control Application in Mechatronics
Abstract: Constrained reinforcement learning is of great practical interest due to the pervasive existence of constraints in applications. Beyond the typical constraints directly on the state space, simulation-based constraints are harder to address, due to noisy and time consuming evaluation on both the performance and the feasibility of a policy. We consider this important problem in this work and make two contributions. First, we develop an algorithm based on Q-learning that iteratively improves the performance and the feasibility of a policy and show its global convergence. Second, for online learning we develop an algorithm to control the sampling among the action space, which is shown to asymptotically maximize the probability of correctly selecting the best feasible action.

Keywords: Modeling and Design of Mechatonic Systems, Actuators, Medical Robotics/Mechatronics
Abstract: One of the major challenges in non-contact actuation of miniaturized medical robots (MMRs) during minimally invasive surgery is precise magnetic force control to ensure accurate movement of these devices inside the human body. This study presents a novel model for the control of the magnetic field generated by a magnetic actuator composed of an electromagnetic coil with a ferromagnetic core. A hybrid model that incorporates analytical formulations of physical phenomena and adapts them based on experimental measurements is used as an alternative approach. This model enables calculation of the in-workspace magnetic field, even in nonlinear conditions associated with high currents in the actuator, offering a significant extension of the operating region. We have experimentally evaluated this model in terms of accuracy, computation time and implementability. The results show that it can be computed accurately in a few milliseconds, making it an ideal choice for controlling magnetic mini-robots.

Keywords: Intelligent Process Automation, Modeling and Design of Mechatonic Systems, Control Application in Mechatronics
Abstract: Automating the sewing process presents significant challenges due to the inherent softness of fabrics and the limited control capabilities of sewing systems. To realize sewing automation, we propose a time-scaling modeling and control architecture of the robotic sewing system. By using the time-scaling modeling, the nonholonomic kinematics of the sewing process of the industrial sewing machine is linearized precisely. Based on this model, a two-layer real-time control architecture is proposed. The upper layer controls the sewn seam line trajectory using the model-based feedback control implemented in the time-scaling domain, while the lower layer controls the manipulator and the sewing machine using geometric-based trajectory generation and coordinated motion control of the robot and the sewing system in the time domain. The experimental results demonstrate that the sewing trajectories exponentially converge to the desired trajectories without overshooting under different initial conditions and sewing speeds. Besides, the same sewing trajectories under different sewing speeds are obtained for a given stitch size. The sewing results show the good performance and application potential of the proposed robotic sewing system.

Keywords: Motion Vibration and Noise Control, Modeling and Design of Mechatonic Systems, Design Optimization in Mechatronics
Abstract: The piezoelectric metamaterials, typically consisting of identical piezoelectric transducers shunted with local resonant circuits, are conceptually appealing for wave attenuation and vibration isolation. Nevertheless, significant barriers exist. The bandgap widths are generally narrow, and the transmission reduction is limited when the number of unit cells is relatively small in practical situations. In particular, most existing investigations focus on the theoretical aspects, and the mechatronic synthesis for validation and implementation is lacking. This research aims at addressing the fundamental challenges in realizing wide-band transmission reduction of piezoelectric metamaterial beams by means of a comprehensive circuitry integration. We first formulate an analytical transmittance analysis in the wave domain which is utilized to elucidate the parametric influence of circuitry integration. We then carry out a systematic experiment-based investigation of the enhanced piezoelectric metamaterial featuring the integration of a tunable synthetic inductance and negative capacitance, in order to achieve improved transmission reduction over a broadened bandgap frequency range. While the negative capacitance is theoretically helpful, it is illustrated that the parasitic resistance will negate its benefit. It is then demonstrated that the subsequent introduction of the negative resistance within the same synthetic impedance circuit can significantly enhance the system performance. This research provides critical insights into the implementation of piezoelectric metamaterials using synthetic impedance circuit integration, which lays the foundation for system-level application of such concepts for wave attenuation and vibration isolation.

Keywords: Actuators in Mechatronic Systems, Design Optimization in Mechatronics, Modeling and Design of Mechatonic Systems
Abstract: For several applications such as robotic joints, it is necessary to simultaneously optimize the torque density, torque ripple, and dynamic response capability of permanent magnet synchronous machines (PMSMs). However, the method for evaluating the dynamic response capability based on the structural parameters of the machine and its co-optimization with the torque performance is not clear. Therefore, this paper takes the PMSM with the same number of poles and slots as the research object and optimize these three objectives simultaneously. Firstly, a generalized electromagnetic performance prediction model for this type of machine with different topologies is proposed based on the improved subdomain model. Additionally, the evaluation model of the dynamic response capability of the PMSM is established by the mechanical and voltage equations. Based on the proposed model, the sensitivity of each parameter to the torque density, torque ripple, and dynamic response capability of the machine is analyzed, and the NSGA-II algorithm is used to optimize these three objectives simultaneously. Finally, the performance of the selected case is verified based on finite elements analysis (FEA), which is improved in all three objectives.

Keywords: Modeling and Design of Mechatonic Systems, Robot Dynamics and Control, Mobile Robots
Abstract: Simulation to reality (sim2real) transfer from a dynamics and controls perspective usually involves re-tuning or adapting the designed algorithms to suit real-world operating conditions, which often violates the performance guarantees established originally. This work presents a generalizable framework for achieving reliable sim2real transfer of autonomy-oriented control systems using multi-model multi-objective robust optimal control synthesis, which lends well to uncertainty handling and disturbance rejection with theoretical guarantees. Particularly, this work is centered around a novel actuation-redundant scaled autonomous vehicle called Nigel, with independent all-wheel drive and independent all-wheel steering architecture, whose enhanced configuration space bodes well for robust control applications. To this end, we present the mechatronic design, dynamics modeling, parameter identification, and robust stabilizing as well as tracking control of Nigel using the proposed framework, with exhaustive experimentation and benchmarking in simulation as well as real-world settings.

Keywords: Flexible Manipulators and Structures, Space Robotics, Modeling and Design of Mechatonic Systems
Abstract: Soft landing on weightless asteroids is challenging in space exploration missions. This paper proposes a cable-driven landing gear system (LGS) with rigid-flexible coupled structures (RFCSs) for the soft landing of a spacecraft on asteroids. The cable-driven mechanism improves the compliance of the spacecraft’s landing legs and has the merits of being lightweight and compact. The RFCS minimizes the impact force of the landing legs when crashing the asteroid’s surface. We designed a three-legged LGS and formulated its kinematics and dynamics. We conducted simulations and experiments of a simplified spacecraft prototype. The results showed that the spacecraft can safely land on rough slopes, with the legs contacting the ground at different sequences. The collision speeds of 10-50 cm/s are verified. This study provides a new idea for the landing and operation of these cable-driven RFCS probes in a weightless environment. The results are valuable for the design of asteroid landers and their stabilizing control.

Keywords: Control Application in Mechatronics, Modeling and Design of Mechatonic Systems
Abstract: This study presents a flume flow experimental investigation of operational performances of a tidal current energy converter (TCEC) with a horizontal-axis tidal turbine (HATT) and an infinitely variable transmission (IVT). A closed-loop speed ratio controller of the IVT is developed to continuously adjust its speed ratio with variable water speeds for a desired constant output speed. Flume flow testing of the TCEC is performed to test validity of the closed-loop speed ratio controller of the IVT under different flow speed conditions. Flume flow testing results show that the speed ratio controller can achieve good control performances with the tracking error less than 2.56% for the given desired output speed. Fluctuations of IVT output speeds caused by variable flow speeds and water turbulence are reduced by more than 91.06% via the continuously varied speed ratio of the IVT and its speed ratio controller. Good operational performances of the IVT can ensure optimal arrangements of operational torques and rotation speeds in the drivetrain of the TCEC with optimal speed ratios under low-speed and high-torque operational conditions.

Keywords: Learning and Neural Control in Mechatronics, Control Application in Mechatronics, Identification and Estimation in Mechatronics
Abstract: Iterative learning control (ILC) yields accurate feedforward input by utilizing experimental data from past iterations. However, typically there exists a trade-off between task-flexibility and tracking-performance. This study aims to develop a learning framework with both high task-flexibility and high tracking-performance by combining rational basis functions and frequency-domain learning. Rational basis functions enable learning of system zeros, enhancing system representation compared to polynomial basis functions. The developed framework is validated through a two-mass motion system, showing high tracking-performance with high task-flexibility, enhanced by the rational basis functions effectively learning the flexible dynamics.

Keywords: Control Application in Mechatronics, Identification and Estimation in Mechatronics, Biomechatronics
Abstract: Prosthetic hands with limited functionality have been abandoned due to individual finger movements and responsiveness issues. Conventional strategies for addressing this issue are expensive and difficult to maintain. Our proposed control strategy uses a hybrid approach with an on-off controller for closing fingers and a robust position controller for opening. We have improved the system's robustness by using linear matrix inequalities machinery and a guaranteed cost full-order filter. We tested this hybrid strategy with three different-sized fingers and three different objects, achieving satisfactory results. This strategy has the potential for future development, showing satisfactory results.

Keywords: Control Application in Mechatronics, Modeling and Design of Mechatonic Systems, Mechatronics in Manufacturing Processes
Abstract: Disturbance rejection of the high-precision scan stages is important in industrial lithography equipment. The aim of this paper is to develop an optimization method for designing multi-axis resonant filters, that enhance the disturbance rejection performance in scanning motion. The developed optimization method explicitly defines resonant filters in structured representation and formulates the data-driven convex optimization problem. The method enables the multi-axis resonant filter design with iterative convex optimization using the frequency response data of the six-degree-of-freedom experimental setup. Experimental results on the industrial large-scale high-precision scan stage demonstrate the performance improvement of the disturbance rejection in the scanning motion using the optimized resonant filters.

Keywords: Control Application in Mechatronics, Identification and Estimation in Mechatronics
Abstract: Linear motors are widely used in the manufacturing industry, in which time-optimal desired motion and high-accuracy motion tracking are both needed for higher productivity and better quality of product produced. However, the unavoidable uncertainties and input/state hard constraints in actual operations make the traditional separate treatment of desired motion planning and high-accuracy motion tracking control either too conservative or causing closed-loop instability. To address these issues, a two-layer control structure is proposed in this paper. In the upper layer, a time-optimal control problem taking into account the system model and hard constraints is solved online instead of off-line to make full use of the accurate parameter estimations and real-time knowledge of the system initial state of lower layer adaptive robust control (ARC) controller. By doing so, not only the conservativeness of traditional off-line motion planning is overcome but also the closed-loop stability of overall system can be guaranteed through seamless integration of the lower layer ARC controller design and upper layer constrained optimization on-line planning. Comparative experiments conducted on a linear motor confirm the effectiveness of the proposed method.

Keywords: Mechatronics in Manufacturing Processes, Actuators in Mechatronic Systems, Flexible Manipulators and Structures
Abstract: A robotic grinding system requires a force-controlled grinding module to provide a consistent surface roughness and a robot arm to position the grinding module to reach a wide range of surface area on a workpiece. Existing pneumatic grinding modules are bulky and energy-inefficient. Existing 6-axis robot arms are often used for grinding positioning, but they require a large accommodation space and have limited access to the surface of a workpiece. This paper proposes a compact 3-axis spherical robot with no grinding surface limitations. The robot has back-drivable actuators and hence can be guided by a human operator to facilitate the path planning of a grinding surface. The proposed grinding module has low reflected inertia and hence can be used to control the grinding force accurately. The proposed grinding module also has a small size, low noise, and minimum energy consumption. Experiments are presented to verify the accuracy of grinding force control. Through an illustration of removing the parting line of a helmet hardshell, the spherical robot is shown to be able to effectively provide grinding treatments on a delicate surface with a wide range of roughness. It is expected that the proposed robot can be widely used in automatic grinding operations.

Keywords: Identification and Estimation in Mechatronics, Hybrid intelligent systems, Mechatronics in Manufacturing Processes
Abstract: This paper presents a physics-informed neural network (PINN) architecture for contextual anomaly detection in a hot forming production line. It enhances widely used proximity- or distribution-based anomaly detection approaches for industrial processes through the consideration of contextual process data. The physical model is built using a priori process knowledge and thermodynamic equations. This model is then injected into the loss function of a neural network. The network is trained on data from the production line and constantly regularized by the physical loss term. Within inference, the PINN predicts the resulting temperature of the produced blank given the contextual process data. The anomaly detection is performed using the unsupervised local outlier factor algorithm on the error between actual and predicted blank temperature. This makes it possible to assess whether the achieved product temperature appears normal or abnormal based on the database. The main advantage of this novel approach is that it is capable of detecting contextual anomalies that remain otherwise undiscovered.

Keywords: Mechatronics in Manufacturing Processes, Compuational Models and Methods, Control Application in Mechatronics
Abstract: This study developed and validated a boss-specific paint deposition model that considers the phenomenon of paint blockage during boss painting. In our previous study, we focused on variations in the film thickness distribution depending on the impact angle and spray distance but did not consider painting on protruding shapes such as bosses. In boss painting, there is a shadow space in which the paint is blocked and difficult to apply. Therefore, we geometrically and mathematically derived the shadow space. To confirm the validity of the boss-specific paint deposition model, qualitative and quantitative evaluations were performed. In the qualitative evaluation, the results of the prediction using the model were compared with the results of computational fluid dynamics and the actual phenomena to confirm whether the prediction was appropriate. For quantitative evaluation, we conducted painting tests on a target with a boss placed in the center of a flat plate and compared the results of actual measurements and predictions to verify the validity of the predictions. Consequently, the results confirmed that the prediction of film thickness using the model appropriately considered paint blockage. The accuracy of the predicted values was also confirmed. Thus, the validity of the proposed model was confirmed.

Keywords: Mechatronics in Manufacturing Processes, Machine Vision
Abstract: In this paper, a computer-vision(CV)-based robotic autonomous part repairing system is developed. Robotic autonomous part repair is needed to retrofit high-value parts such as jet engine blade as robotic-based machining system offers advantages in manufacturing flexibility, adaptability, precision, and low cost. Although CV-based robotic manipulation has been explored for applications such as grasping and human-robot interaction, challenges emerge in CV-based robotic machining applications due to the more stringent precision and accuracy in part identification, the inevitable eccentric misalignment in the acquisition of data from the scanning of a rotated part, the artifacts of the laser-scanned data, and the needs for simultaneous force and path tracking at high precision. The contribution of this work is the development of an experimental-based approach to quantify and compensate for the eccentric misalignment, and then, identify and quantify the defect on the part. We illustrate the function and performance of the CV-based robotic autonomous repairing through experiment.

Keywords: Mechatronics in Manufacturing Processes, Novel Industry Applications of Mechatroinics
Abstract: This paper presents the design and implementation of a compact Automated Fiber Placement (AFP) head, addressing the limitations of conventional large AFP heads in small workspaces and complex shapes production. Traditional AFP heads, typically large and bulky, increase costs and require significant workspace, often leading to manual fiber placement that compromises product quality. Our design, developed at Concordia University, encompasses mechanical design, circuitry, and software, offering a viable solution for efficient fiber placement of a V-shape thermoset part. The experimental results show that the designed AFP head can manufacture the V-shape structure with a minimum angle of around 96 degrees and a radius of 7.5mm.

Keywords: Parallel Mechanisms, Mechatronics in Manufacturing Processes, Robot Dynamics and Control
Abstract: Pick-and-place automation requires robots to have at least three translational (3T) and one rotational (1R) degrees of freedom. Parallel robots usually include four limbs connected to a traveling plate to generate 3T1R motion. For the four limbs to be arranged with rotational symmetry, complicated types of passive joints and traveling plates are required, which make 3T1R robots structurally weaker and prone to wear and clearance issues. This paper presents a new 3T1R parallel robot that uses only revolute joints as the active and passive joints. Compared with other joint types, revolute joints are structurally simpler and stronger. They have an unlimited range of motion and can be preloaded to eliminate clearance. The proposed robot allows the four limbs to be connected with rotational symmetry. Compliance analysis shows that the 4-DoF robot has a homogenous compliance distribution. Experiments are given to verify that the robot can achieve low structural compliance when compared with existing counterparts. The robot is expected to provide an alternative solution in pick-and-place applications.

Keywords: Vehicle Technology
Abstract: In recent years, wireless power transfer (WPT) has become popular from the viewpoint of easy charging. Among them, magnetic field resonance WPT is being researched and developed due to its high efficiency. However, there are magnetic fluxes that cannot be used for power supply and are leaking out in magnetic field resonance WPT. Therefore, this paper applies a special magnet arrangement, a Halbach array, for transmission coils. The Halbach array transmission coils can concentrate the magnetic fluxes on one side. This feature allows the magnetic fluxes to be concentrated to increase the amount of magnetic fluxes chained to the receiving coil. It has a significant effect on efficiency. Since the size of the transmission and receiving coils also affects efficiency, this paper changes the size of the coils and analyzes its effect on efficiency. The efficiency of the Halbach array transmission coils will be confirmed by comparison with conventional transmission coils.

Keywords: Planning and Navigation, Vehicle Control, Design Optimization in Mechatronics
Abstract: In recent years, there has been a growing interest in smart agriculture, aimed at enhancing efficiency in farming through the use of technology. Farmers, working with multiple machines across various fields, necessitate the development of a versatile task assignment and route generation system (task allocation system) to cater to a diverse range of conditions. Previous studies have proposed various methods to address this problem. However, it remains unclear which method is most suitable when specific conditions tailored to individual farms are considered. Additionally, the performance of these methods is not fully utilized as hyperparameters are often set empirically. Consequently, the development of a truly versatile task allocation system for agriculture remains unachieved. Therefore, this study aims to develop a versatile task allocation system for agriculture. Specifically, we created “the field nodes divided graph” by dividing fields into the maximum number of vehicles operating in that field, and by formalizing it as a split delivery vehicle routing problem (SDVRP), we modeled the farmland considering the operation of multiple vehicles. Using computer simulations, this study identifies the most effective optimization methods and hyperparameter combinations under varying farm sizes and maximum calculation times. The results of computer simulations applying a local search method, a simulated annealing (SA), a genetic algorithm (GA), and an ant colony optimization (ACO) to five types of hypothetical grid-shaped farmlands revealed that the SA algorithm is superior for smaller farmlands, while the local search method excel in larger farmlands with shorter calculation times. Furthermore, the study derives the best hyperparameter values corresponding to different farm sizes.

Keywords: Planning and Navigation, Transportation Systems, Mobile Robots
Abstract: This paper presents a pedestrian flow estimation and its application to a self-driving electric wheelchair to realize locomotion adapting to crowd flow. In recent years, obstacle avoidance control of vehicles in urban areas has been intensively studied. However, the vehicle must better drive in accordance with nearby pedestrian movement to avoid disrupting traffic. In this study, we estimate the surrounding pedestrian traffic flow via the data assimilation based on the Kalman filter using a LiDAR sensor that obtains point clouds appearing on observable pedestrians. Then, we utilize the estimated flow to the self-driving controller of an electric wheelchair. The effectiveness is verified via the self-driving electric wheelchair built on a simulator that realizes pedestrian dynamics reflecting the social force model.

Keywords: Automotive Systems, Transportation Systems, Mobile Robots
Abstract: Autonomous vehicle platforms of varying spatial scales are employed within the research and development spectrum based on space, safety and monetary constraints. However, deploying and validating autonomy algorithms across varying operational scales presents challenges due to scale-specific dynamics, sensor integration complexities, computational constraints, regulatory considerations, environmental variability, interaction with other traffic participants and scalability concerns. In such a milieu, this work focuses on developing a unified framework for modeling and simulating digital twins of autonomous vehicle platforms across different scales and operational design domains (ODDs) to help support the streamlined development and validation of autonomy software stacks. Particularly, this work discusses the development of digital twin representations of 4 autonomous ground vehicles, which span across 3 different scales and target 3 distinct ODDs. We study the adoption of these autonomy-oriented digital twins to deploy a common autonomy software stack with an aim of end-to-end map-based navigation to achieve the ODD-specific objective(s) for each vehicle. Finally, we also discuss the flexibility of the proposed framework to support virtual, hybrid as well as physical testing with seamless sim2real transfer.

Keywords: Vehicle Control, Vehicle Technology, Control Application in Mechatronics
Abstract: The number of poles and speed of permanent magnet synchronous motors (PMSMs) for electric vehicles (EVs) are increasing along with the development of higher power density PMSMs. Therefore, the switching-to-fundamental frequency ratios (SFRs) becomes lower at a regular switching frequency of the inverter. However, a low SFRs deteriorates the dynamic response of the current controller. Meanwhile, suppressing the torque ripple using harmonic injection becomes challenging. To address this issue, this study proposes a current controller with excellent tracking performance even at a low SFRs. Specifically, the dynamic response performance of the current controller is enhanced using the perfect tracking control (PTC) based on the double-update pulse width modulation (PWM) method. The proposed method is tested through numerical simulation, and an experiment is conducted using he surface-mounted permanent magnet synchronous motor (SPMSM). The results demonstrate that the proposed controller exhibits superior tracking performance compared to conventional methods.

Keywords: Network Robotics
Abstract: This paper investigates the problem of distributed multi-leader formation tracking of a multi-agent system within a directed network that may be weight-unbalanced. We propose distributed formation tracking algorithms with offline estimators. Under the assumptions that the communication network of the follower agents is strongly connected and each leader agent is accessible by at least one follower agent, all follower agents asymptotically track the center of the leader agents with a time-varying formation offset. Simulation is performed to substantiate the theoretical conclusion.

Keywords: Network Robotics, Control Application in Mechatronics, Intelligent Process Automation
Abstract: Orthogonal Frequency-Division Multiple Access (OFDMA) is a feature implemented in IEEE 802.11ax (Wi-Fi 6) that aims to improve performance by sending packets simultaneously to multiple users. This paper highlights performance issues when using OFDMA with a real-time control application based on the commonly used transmission control protocol (TCP). OFDMA is designed to send data to multiple users simultaneously with reduced latency by utilizing many sub-carrier frequencies grouped into resource unit (RU) blocks. However, we found that when using a TCP data stream subject to a variable update rate from late packets, the OFDMA algorithm under test was not sufficient to improve performance, and instead increased latency. This surprising finding may pose a concern for industrial applications that rely on TCP transport. We performed experiments to compare the latency and physical performance results of OFDMA to OFDMA turned off as well as our previous works which utilized wireless time-sensitive networking (TSN) features implemented in software. The previous wireless TSN results demonstrated close to deterministic latencies for a TCP link subject to inter-network interfering traffic.

Keywords: Tele-operation, Compuational Models and Methods
Abstract: Shared autonomy is a robot control approach that assists human users to achieve their intended goal while leveraging the precision and efficiency of robot autonomy. In shared autonomy, user input and autonomous assistance are combined to effectively control robots without requiring users to provide direct and precise control inputs. A persistent question in shared autonomy is how to determine the arbitration between user input and autonomous algorithm. Due to variability in users' desired amount of assistance, it is imperative to develop user-centric algorithms that provide customized and adaptive assistance by considering users' preference, physical capability, and expertise. In this paper, we propose a shared autonomy method that factors in both users' task performance and level of expertise to adaptively adjust the amount of assistance at runtime. We validated our method in an assistive control problem where human users teleoperate a robotic arm to perform object reaching and grasping tasks in a simulated environment. The results show that our method assisted the users to achieve a higher efficiency in accomplishing the object reaching and grasping tasks compared to direct teleoperation and two baseline arbitration methods that only consider task-related metrics.

Keywords: Tele-operation, Micro/Nano Manipulation, Micro-Electro-Mechanical Systems
Abstract: In micro-manipulations such as cell manipulation, it is desirable for the operator to feel the haptic sensation of the object. Bilateral control can remotely transmit position and force information between leader and follower systems. In this control, the use of a linear motor as a leader and a stacked piezoelectric actuator as a follower has been proposed to achieve micro-scale operation. There is a lot that needs to be clarified about bilateral control when the structure differs between leader and follower systems. In conventional scaled 4-channel (4ch) bilateral control, a theory of oblique coordinate control has been proposed that considers differences in the inertia of leader and follower systems. However, when a piezoelectric actuator is used, the control scheme differs from using two linear motors with different inertias because the structures of the leader and follower systems are entirely different. Another method is scaled admittance bilateral control. However, the control design when structures and inertias of the two systems are different has not yet been clarified. In this paper, a scaled admittance bilateral control using a piezoelectric actuator and a linear motor is constructed. Experiments confirm that the realized scaled admittance bilateral control has the equivalent position and force tracking performances as the conventional scaled 4ch bilateral control using a piezoelectric actuator. Furthermore, the designed scaled admittance bilateral control is more robust to fluctuations in the nominal inertia of the piezoelectric actuator than the conventional scaled 4ch bilateral control.

Keywords: Tele-operation, Vehicle Technology, Machine Vision
Abstract: Real-time teleoperation of robotic systems over the Internet is a desirable technology in many ways. Latency of the video feedback has been hampering its development. This paper takes the application of remote driving to introduce an unconventional codec that provides a very low latency for Internet-based video streaming. The proposed method preserves just enough information in the video for essential perception and decision making of a remote driver. Thanks to a unique integration of several image processing and data streaming techniques, the proposed codec can realize a glass-to-glass latency around 90ms. A series of tests are conducted over the real consumer Internet to analyze the latency and verify the effectiveness of remote driving with the proposed codec.

Keywords: Network Robotics, Part Feeding and Object Handling 
Abstract: Bio-inspired decentralized approaches for transporting objects with robot networks seek to use locally-sensed information such as object-robot interaction forces, without the need for robot-to-robot communication. However, the design of the decentralized controller to achieve a specified network performance (e.g., to achieve a desired network settling time Ts) depends on the particular network/object connectivity and therefore tends to be a centralized decision. Such centralized controller design is not biomimetic and might not be viable if communication is not available between agents to achieve decentralized consensus on the controller parameters. The main contribution of this article is a decentralized controller design approach using local measurements, which does not require prior knowledge of the robot network or object properties. Rather, only the desired network-level performance (such as network settling time) is needed to select controller parameters with the proposed delayed self-reinforcement (DSR) approach, which decentralizes the ideal case where each robot has information about the transport task. Additionally, experimental results show that the decentralized design with DSR achieves a network settling time of 7.8s that is close the desired value of 10s. Moreover, the DSR approach (with decentralized parameter selection) reduces deformation substantially (by 66%) when compared to the standard (without DSR) case even with centralized design of parameters.

Keywords: Robot Dynamics and Control, Compuational Models and Methods, Vehicle Control
Abstract: When a crane lifts a payload, there are complex dynamic effects that occur as the payload transitions from being supported underneath by its original support surface to being supported above by the overhead rigging. For example, when payloads are lifted off the ground, the payload may unexpectedly swing sideways. This occurs when the payload is not directly beneath the hoist and the hoist cables are at an angle relative to vertical. The dynamics become even more complicated when a payload is held in a jig or structure that applies forces to the sides of the payload during lift, rather than simply resting on a ground surface. Such lift-off effects occur during the dangerous activity of tower crane disassembly when the various parts of the tower crane are removed one-by-one by a mobile telescopic boom crane. The assisting boom crane must attempt to maneuver its endpoint directly over top of the rigging connection point before it can remove each section without inducing complex lift-off dynamic effects. This paper presents a model to predict the lift-off dynamic effects when the assist crane is not positioned perfectly overhead. The model can be used to assess what range of offset angles are relatively innocuous and also to identify conditions that would lead to increased challenges in a lift-off process. The model can be integrated into a control system that performs autonomous-centering solutions to mitigate the detrimental effects of off-centered lifts during tower crane disassembly.

Keywords: Robot Dynamics and Control, Mobile Robots, Design Optimization in Mechatronics
Abstract: Future planetary explorations require versatile robots to adaptively traverse extreme access environments with optimal energy-consumption to address the current rovers’ limitations. This paper discusses a study of the dynamics and velocity-based optimization for planar snake-robot muscle-driven locomotion. The system has two adjacent links connected by a pair of pneumatic artificial muscle (PAMs) series with extension springs. An alternate actuation of PAMs causes rotational motion about the connecting joint. The robot’s kinematics in the joint and Cartesian space were derived with respect to the muscle motion. The robot’s dynamic model were obtained for an N-Link system using Lagrangian mechanics. The performance of the dynamic model was then demonstrated through a MATLAB simulation for a two-link robot. Additionally, a velocity-based optimization was done to analyze the optimal linkage’s geometric parameters and dynamical model properties that yields optimal forward velocity.

Keywords: Robot Dynamics and Control, Identification and Estimation in Mechatronics, Motion Vibration and Noise Control
Abstract: The structural flexibility of industrial robot arms makes them vibrate when they are commanded to move at fast operation speeds. Among the control strategies, feedforward control stands out as an interesting approach to suppress vibration since it does not create stability issues and works for repeating and non-repeating tasks. Currently, the state-of-the-art feedforward controller dedicated to suppressing residual vibration in robot arms is time-varying input shaping (TVIP). However, TVIP falls short in trajectory tracking tasks since the method adds delays in the commands creating errors in tracking and thereby contouring trajectories. Therefore, this paper proposes the use of an alternate feedforward method, known as the filtered B-splines (FBS) approach, to suppress vibration in six DOF robots while maintaining tracking accuracy. Since time-varying FBS (TVFBS) requires full frequency response functions (FRFs), compared to only natural frequencies and damping ratios for TVIP, we propose a framework for estimating the FRFs of serial kinematic chain 6-degree-of-freedom robots. Residual vibration reduction experiments and trajectory tracking experiments, in which the dynamics of a UR5e collaborative robot change considerably, were carried out to validate the model prediction framework. TVFBS reduced the end-effector vibration by 87% while improving tracking performance in both y (22%) and z (29%) directions. On the other hand, TVIP worsened the tracking performance (-683.43% for y and -662.37% for z directions) despite the excellent vibration reduction (98%). Hence, TVFBS demonstrated significantly better tracking performance than TVIP while retaining comparable vibration reduction.

Keywords: Humanoid Robots, Robot Dynamics and Control, Legged Robots
Abstract: Despite major advancements in control design that are robust to unplanned disturbances, bipedal robots are still susceptible to falling over and struggle to negotiate rough terrains. By utilizing thrusters in our bipedal robot, we can perform additional posture manipulation and expand the modes of locomotion to enhance the robot's stability and ability to negotiate rough and difficult-to-navigate terrains. In this paper, we present our efforts in designing a controller based on capture point control for our thruster-assisted walking model named Harpy and explore its control design possibilities. While capture point control based on centroidal models for bipedal systems has been extensively studied, the incorporation of external forces that can influence the dynamics of linear inverted pendulum models, often used in capture point-based works, has not been explored before. The inclusion of these external forces can lead to interesting interpretations of locomotion, such as virtual buoyancy studied in aquatic-legged locomotion. This paper outlines the dynamical model of our robot, the capture point method we use to assist the upper body stabilization, and the simulation work done to show the controller's feasibility.

Keywords: Robot Dynamics and Control, Control Application in Mechatronics, Vehicle Control
Abstract: This paper considers the control of the quadrotors with the unaligned thrust. Unlike the conventional quadrotor, the translational dynamics of these vehicles are sophisticatedly correlated with the rotational dynamics. This arises because the bearing of the total thrust in the body frame varies, in contrast to the unidirectional total thrust of regular quadrotors. This complexity poses a significant challenge to the control design for the quadrotor with the unaligned propellers. To address the challenge, we propose a geometric tracking control method that compensates for the thrust direction variation by incorporating additional vehicle inclination. The nonlinear tracking controller is characterized by defining the tracking error on the special Euclidean group SE(3). Through Lyapunov analysis, we proved almost globally exponential stability of zero equilibrium of the error dynamics. Simulation results illustrate the success of the proposed tracking control in achieving spiral trajectory tracking and recovering from the initial upside-down orientation for quadrotors with distinct propeller alignment configurations.

Keywords: Robot Dynamics and Control, Image Processing
Abstract: Mountain tunnel excavation has two problems, which are a shortage of skilled engineers and frequent industrial accidents. Automation of mountain tunnel excavation is progressing to solve these problems. However, loading explosives in mountain tunnel excavation is difficult to automate because this task requires a sense of force. Motion reproduction is an expected method to automate the process of loading explosives that takes the sense of force into account. It uses bilateral control to save and reproduce motions and has the advantage of being able to reproduce forces and teach human skills to manipulators. On the other hand, motion reproduction cannot succeed in saved tasks when the relative position of the loading hole and manipulator or the direction of the loading hole changes from the saving phase. Therefore, this paper proposes a method to compensate for variations in relative position and direction by image processing based on depth information in motion reproduction for automation of loading explosives. Experiments showed the effectiveness of the proposed method through the successful reproduction of the insertion motion despite variations in relative position and direction.

Keywords: Legged Robots, Modeling and Design of Mechatonic Systems, Walking Machines
Abstract: To promote the research in compliant quadrupedal locomotion, especially with parallel elasticity, we present Delft E-Go, which is an easily accessible quadruped that combines the Unitree Go1 with open-source mechanical add-ons and control architecture. Implementing this novel system required a combination of technical work and scientific innovation. First, a dedicated parallel spring with adjustable rest length is designed to strengthen each actuated joint. Then, a novel 3D dual spring-loaded inverted pendulum model is proposed to characterize the compliant locomotion dynamics, decoupling the actuation with parallel compliance. Based on this template model, trajectory optimization is employed to generate optimal explosive motion without requiring reference defined in advance. To complete the system, a torque controller with anticipatory compensation is adopted for motion tracking. Extensive hardware experiments in multiple scenarios, such as trotting across uneven terrains, efficient walking, and explosive pronking, demonstrate the system's reliability, energy benefits of parallel compliance, and enhanced locomotion capability. Particularly, we demonstrate for the first time the controlled pronking of a quadruped with asymmetric legs with this novel system.

Keywords: Sensors and Sensing Systems, Modeling and Design of Mechatonic Systems, Biomechatronics
Abstract: In numerous fields that analyze the human body from a biomechanical perspective, the force of muscles could only be indirectly estimated through multiple hierarchical levels, and the limitations in terms of accuracy were clear for each methodology. Accordingly, this study introduces a novel, non-invasive method for estimating muscle force, leveraging the phenomenon that transverse muscle stiffness increases under more longitudinal tension. By manufacturing the soft pneumatic sensor system for plantar flexor, the two-step model that can fully describe the interaction between the air cell and muscle is developed. Initially, equations incorporating geometric constraints and force equilibrium are derived to calculate the muscle’s deformation depth from the measured pressure. The correlation between muscle fiber deformation and the transverse reaction force is then identified. Using the proposed model, pressure measurement from sensor system is converted to force estimate. Experimental validation demonstrates its high estimation accuracy, supporting the effectiveness of the proposed model-based approach. This methodology shows promise for diverse fields that require non-invasive and accurate plantar flexor muscle force estimation.

Keywords: Modeling and Design of Mechatonic Systems, Parallel Mechanisms, Humanoid Robots
Abstract: Manipulators applied in daily life, like exoskeletons or humanoid robots, always require excellent comprehensive performance comparable to or even surpassing that of humans to deal with diverse tasks. However, it is quite challenging to achieve all the performance simultaneously. This paper presents a design paradigm to enable manipulation systems with favorable comprehensive performance of high payload, repeatability, and bandwidth. A novel 3-RRR coaxial spherical parallel mechanism (SPM) was realized to achieve high payload and bandwidth. Structure optimization was conducted to improve the torque output performance and expand the workspace. High-performance actuators, known for their high torque and bandwidth, were designed to ensure a high upper bound of overall system performance. A linkage transmission mechanism with high stiffness was employed to ensure a high repeatability. The prototype designed under the paradigm featured human size and provided favorable performance of 10 kg payload with arm fully straight, repeatability within 0.5 mm, and 11.9 Hz for position control bandwidth.

Keywords: Medical Robotics/Mechatronics, Modeling and Design of Mechatonic Systems
Abstract: Robotic steering can be useful in the placement of electrodes in spinal cord stimulation (SCS) and dorsal root ganglion stimulation (DRGS) procedures. This paper introduces an innovative steering and latching mechanism called the ExoNav, designed for spinal cord stimulation electrodes. By applying magnetic locking in the robotic system, a non-contact stabilization is established at the robot's base to reduce tendon-sheath coupling effects that are common in continuum robots. A kinematic model has been developed and validated to predict the robot's behavior when subjected to tendon actuation. To broaden the analysis, a comparative assessment is performed by comparing this experimental setup with scenarios involving a free base and another with immobilization using an external magnet. Finally, proof-of-concept trials with a surgeon demonstrate the capability of the ExoNav robot in phantom spinal cord models.

Keywords: Modeling and Design of Mechatonic Systems, Design Optimization in Mechatronics, Parallel Mechanisms
Abstract: In the structure of a palletizing robot, auxiliary links are generally used to drive rotational links and maintain the horizontal orientation of the robot end-effector. However, with recent developments in manufacturing technologies and the increasing diversity of tasks, there is a demand for reducing the space occupied by auxiliary links with lightweight robot designs. In this study, a new method to reduce the size and weight of palletizing robots by replacing the existing auxiliary links with cable-actuation is proposed. First, the kinematics of a palletizing robot with parallelogram linkages based on geared rolling joints is explained. Additionally, the effects of multiple cable windings on the joint speed reduction are examined. A theoretical analysis of the relationship between the joint angle and cable length confirms that serially connected geared parallelograms can decouple joint motion. Furthermore, the effect of the cable length from the motor to the actuation joint on the stiffness is analyzed. Finally, experiments are conducted using a manufactured robot prototype to verify the effectiveness of cable windings, decoupled joint motion, and robot stiffness, and to confirm the accuracy of distal position and orientation. Consequently, the proposed cable-actuated palletizing robot is expected to be applied in various industrial robot designs.

Keywords: Rehabilitation Robots, Service Robots, Medical Robotics/Mechatronics
Abstract: The super redundant robot has the natural flexibility and passive adaptability, which shows great potential for development in medical care. However, this feature also makes its telescopic and load carrying capacity weak, difficult to complete fine care operations and daily grasping tasks. In this paper, a large telescopic ratio variable stiffness super redundant robot is proposed. The robot has a large telescopic ratio and based on the bionic muscle driven variable stiffness theory, the stiffness of the super redundant robot can be adjusted in a large range. Based on the analysis of origami theory, the robot uses rigid origami mechanisms as the skeleton support, flexible gasbags as the spines, and the hybrid actuation is used to realize the telescopic, variable stiffness and omnidirectional bending motion. The characteristics of the single joint and the 6-joint super redundant robot are verified by experiments. These experiments confirm that the super redundant robot has a large telescopic and variable stiffness range, obtains a large bending deformation and working range, and can overcome the gravity generated by itself and the load, and has a high load capacity.

Keywords: Robot Dynamics and Control, Control Application in Mechatronics, Actuators in Mechatronic Systems
Abstract: This paper introduces a unique force control and adaptation algorithm for a lightweight and low-complexity five-fingered robotic hand, namely an Integrated-Finger Robotic Hand (IFRH). The force control and adaptation algorithm is intuitive to design, easy to implement, and improves the grasping functionality through feedforward adaptation automatically. Specifically, we extended Youla-parameterization which is traditionally used in feedback controller design into a feedforward iterative learning control algorithm (ILC). The uniqueness of such an extension is that both the feedback and feedforward controllers are parameterized over one unified design parameter which can be easily customized based on the desired closed-loop performance. While Youla-parameterization and ILC have been explored in the past on various applications, our unique parameterization and computational methods make the design intuitive and easy to implement. This provides both robust and adaptive learning capabilities, and our application rivals the complexity of many robotic hand control systems. Extensive experimental tests have been conducted to validate the effectiveness of our method.

Keywords: Control Application in Mechatronics, Robot Dynamics and Control
Abstract: The technology of soft continuum robots represents an advance in the field of robotics to benefit a wide range of industries such as healthcare, manufacturing or environmental exploration. Due to their compliant continuous structure, they are adaptive to environmental conditions and thus beneficial for physical human-robot interaction (pHRI). The use of pneumatic actuation offers crucial safety benefits for pHRI due to its direct drive characteristics and its inherent compliance by the compressibility of air. In this paper, an interaction-friendly, optimization-based method for offline trajectory generation of pneumatic soft continuum manipulators for allowing undesired and desired interactions in the context of pHRI is derived and validated experimentally on a handling task performed by the bionic soft arm. The interaction-friendly criteria are mainly described by the manipulator's stiffness and the detectability of external forces, which are considered in a two-step optimal control problem for the free movement and the contact approach of the bionic soft arm. The resulting optimal trajectories of the joint angles and joint stiffnesses are compared with time-optimal trajectories and discussed. From the measurements, it can be concluded that the presented method exploits the redundancies of the differential pressure actuation and the properties of the manipulator to achieve interaction-friendly trajectories.

Keywords: Intelligent Process Automation, Control Application in Mechatronics, Rapid Prototyping
Abstract: 3D concrete printing is becoming increasingly prevalent in the construction industry. One of the primary challenges associated with this printing process is achieving high quality external appearance, primarily determined by the consistency of the filament size. Previous research has focused primarily on developing specific materials tailored to particular environments. However, variations in environmental temperature can significantly affect the curing process and the properties of the fresh material. To enhance the printing quality while taking into account the constraints imposed by the filament extrusion process on continuous trajectories and disturbances in real printing conditions (uncontrolled environment), this paper proposes a control method based on adaptive adjustment of the deposition velocity. This method reduces deposition defects by considering the thermo-mechanical properties of the material, the geometric aspects of the shape, and the process parameters in uncontrolled environments. To assess the effectiveness of this strategy, nine tests were carried out and compared in different emulated environments using a climate chamber, with three temperature levels: 10, 20 and 30 degrees Celcius.

Keywords: Control Application in Mechatronics
Abstract: In industrial positioning systems where rapid response and high-precision are crucial, minor model inaccuracies due to unknown dynamics and identification errors in controller design significantly impede achieving desired positioning accuracy. This paper presents and evaluates a direct data-driven control-based additional feedforward (FF) compensation method, aimed at enhancing precision in positioning while streamlining the design process. The purpose of this additional FF compensation is to attenuate undesirable error responses resulting from unknown modeling errors in the existing model-based FF design. The presented method enhances control performance by utilizing data-driven prediction of positioning response and optimizing the predicted response. The effectiveness of the presented approach is substantiated through comprehensive experiments with a galvano scanner in printed circuit board laser drilling applications, demonstrating significant improvements in positioning accuracy and response time.

Keywords: Control Application in Mechatronics, Identification and Estimation in Mechatronics, Actuators
Abstract: This study entailed the derivation of an inverse airflow dynamics model that causes pneumatic transmission delay due to the long air tube in pneumatic artificial muscle (PAM) control. The inverse model of the derived airflow dynamics was used in designing a feedforward pressure control command for the proportional pressure control valve. We also modulated the feedback command based on the proposed pressure control for precise force tracking performance. The proposed methods were validated by varying the tube lengths in the pressure tracking task and force tracking task. The tracking tasks with the sinusoidal desired profile of 2.5 Hz were successfully achieved using the proposed method. The results indicate that the proposed method can compensate for the delay due to the airflow dynamics in the long air tube and improve the control performance.