Keywords: Mechatronics in Manufacturing Processes
Abstract: Driven by the exponential growth of data from widespread deployment of sensors and the continued advancement of computational infrastructure, AI/machine learning has been continually transforming the state of mechanical, electrical, and computer engineering. The transformation has led to a data-driven paradigm that complements and augments model-based techniques in the design and optimization of mechatronic systems for information acquisition, optimization, and control. The outcome is improved functionality, efficiency, and reliability of mechatronic systems to advance the state of smart manufacturing.

This presentation traces the data-enabled pathway towards integrating physics-based and data-driven methods for mechatronic systems in manufacturing. Recent progress in sensing, process monitoring, and process control enabled by this integration is illustrated. New research trends, such as concerted hardware-software co-design, are discussed. The presentation demonstrates the potential of data-driven methods as a key enabler to complement physical science for advancing mechatronics in realizing smart manufacturing.

Keywords: Aerial Robots, Identification and Estimation in Mechatronics, Sensor Integration, Data Fusion
Abstract: Small aerial vehicles have great potential for applications such as manufacturing, logistics, and wildlife surveys. However, their limited payload capacity and endurance pose significant challenges for onboard sensing and navigation, especially for millimeter- to centimeter-scale flyers. This work offers a sensing and control strategy for a small quadrotor to achieve reactive autonomy, defined as flying and avoiding collisions. This relies on a minimal suite of sensors typically employed for hovering flight only. We analyze and model the aerodynamic interactions between propellers and nearby walls, which are amplified by the robot's ducted propellers. The results are integrated with flight dynamics to enable the robot to estimate wall distance and direction. A flight controller is devised to safely stabilize the robot near a wall. Together, the sensing and control framework allows the robot to react, fly, and avoid collisions without extra sensors or visual-inertial navigation.

Keywords: Unmanned Aerial Vehicles, Robot Dynamics and Control, Actuators
Abstract: In this paper, the problems associated with UAVs and torsional tasks constraints regarding valve turning are addressed. An add-on thrust vectoring device which enhances manipulation options available to a conventional multirotor UAV is developed and described. We further expand this concept, by presenting two design configurations for a thrust vectoring device, which allows a UAV to perform torsional work. A high torque configuration composed of three electric ducted fans allow for a torsional moment to be generated in the z axis. A dual torque configuration composed of two electric ducted fans which allows the torsional moment to be oriented around the frame of the UAV The proposed system expands the aerial manipulation options available to a conventional multirotor UAV, as well as the forces the vehicle can generate. The experimental results illustrate the forces and torques that can be generated independent of the UAV's orientation.

Keywords: Control Application in Mechatronics, Unmanned Aerial Vehicles, Network Robotics
Abstract: In this study, we address the analysis of the collective behavior of a swarm of dynamic agents under the control of a generalized cyclic pursuit (GCP) scheme. The detailed features of this study are as follows. First, the generalized frequency variable (GFV) is used to show how a dynamic multi-agent system, whose collective behavior is guided by the GCP scheme, may be formulated into the LTI system framework. Then, we examine the stability, instability, and marginal stability of the dynamic multi-agent systems under discussion using a graphical framework based on the stability analysis of a general LTI system with GFV. Second, although the suggested graphical analysis framework is highly proficient in anticipating rendezvous or diverging spiral motions of GCP-controlled dynamic multi-agent systems, it may prove challenging to precisely predict whether a group of dynamic agents will move in a circular or spirograph-like fashion. Therefore, an analytical tool is developed to overcome the limitations of the graphical technique. Third, we describe the steady-state formation trajectories of a swarm of GCP controlled dynamic agents by explicitly taking into account their general continuous-time LTI model and the case where there are more than two pairs of closed-loop poles on the imaginary axis of the complex plane. Additionally, we discuss the analytical standards for evaluating the spirograph-like closed and open orbits that correspond with the dynamic agents’ steady-state trajectories. Lastly, the study presents comprehensive simulation results that demonstrate the validity of the developed analytical methodologies.

Keywords: Network Robotics, Planning and Navigation, Robot Dynamics and Control
Abstract: This work presents a new delayed-self-reinforcement (DSR) control approach for human-led multi-robot platooning through an area with obstacles. Recent works have shown that with the use of DSR-based approaches, the velocity cohesion and robustness of the vehicle platooning can be improved. However, it only applies to the 1-dimensional longitudinal control. This work further extends the applications of the DSR-based approach in the 2-dimensional space on a mobile robot network, by combining the DSR approach with the trajectory planning based on Bezier Curve. With the 2-dimensional estimated trajectory of the predecessor projected to the 1-dimensional curve, the DSR approach greatly reduces the tracking error on the 1-dimensional space of the target trajectory. The proposed method only uses the local sensing information of the current and historical steps. Comparative simulation results show that both the longitudinal and lateral tracking errors are reduced by 99% and 85% with the use of DSR approach during transitions, compared to the case using standard dynamical feedback linearization but without the use of DSR.

Keywords: Mobile Robots, Control Application in Mechatronics, Robot Dynamics and Control
Abstract: This paper presents the design and control of a solar panel cleaning mobile robot carried by a drone. The robot has tracked wheels to stick to the slanted solar panels and move. Control between suction pad and wheel velocities has to be done with care in order not to slip down while moving. Experimental studies of moving on the solar panel were demonstrated to confirm the feasibility.

Keywords: Mobile Robots, Sensors and Sensing Systems, Robot Dynamics and Control
Abstract: This work focuses on exploiting the concept of ergodicity for motion planning to effectively guide emergency responders or emergency deployed unmanned autonomous systems (UAS) to search and locate a buried snow-avalanche victim. Statistics show that 90% survival rate occurs when an avalanche victim is located within 15 minutes of being buried. As interest in exploiting UAS for first response increases, effective search algorithms for autonomous robotics can help improve search and rescue. A new motion planning algorithm that utilizes ergodic exploration and information theory is developed where the optimization process considers robot dynamics. As the robot agent explores, sensor measurements are processed by a Bayesian filter for victim localization. Compared to existing similar approaches, the proposed search method systematically maximizes information gain and ensures that search trajectories are dynamically feasible. Simulation results are presented to demonstrate the performance of the algorithm for estimating and localizing a buried snow-avalanche victim.

Keywords: Network Robotics, Part Feeding and Object Handling , Flexible Manipulators and Structures
Abstract: This work presents new control approaches for flexible object transport using robot networks. Recent works have investigated bio-inspired strategies to transport objects using decentralized robot networks that only use local measurements without the need for communication between robots [1], [2]. However, current decentralized theories focus on ensuring state consensus at the end of the transition and not during transition. Deviation of states during transition causes large deformation, which can lead to damage of the object transported. With current methods, deformation can only be reduced by increasing the transport time. In contrast, this work develops a delayed self- reinforcement (DSR) [3] approach for transport tasks to reduce deformation during transport of flexible objects, without increasing transport time. An advantage of the DSR method is that it only uses a delayed self reinforcement of each robot’s actions using prior available data and does not require additional information from the network. Furthermore, experimental results are presented to show that the proposed DSR-based transport method can reduce the deformation by at least 75% for the same transport time, when compared to the case without DSR.

Keywords: Planning and Navigation, Mobile Robots, Service Robots
Abstract: This paper presents a navigation strategy for an autonomous forklift used in automated warehouse. The linear segments parabolic blends-based trajectory planner and model predictive control-based motion controller are designed. The performance of the suggested method is demonstrated via Matlab simulations in a warehouse environment.

Keywords: Planning and Navigation, Robot Dynamics and Control, Mobile Robots
Abstract: This study introduces a dynamic inversion based trajectory planning algorithm for wheeled inverted pendulum (WIP) robots that incorporates a linear joint atop the WIP body. We utilize the singular perturbation technique to obtain an asymptotic series solution for the inverse joint trajectory, while considering kinematic and dynamic constraints.

Keywords: Legged Robots, Robot Dynamics and Control, Control Application in Mechatronics
Abstract: We present Late Breaking Results on achieving robust quadrupedal locomotion by stabilizing a hybrid-linear inverted pendulum (H-LIP) stepping on surfaces with vertical motion. Our framework analyzes H-LIP stability, derives feasible and stable footsteps using quadratic programming (QP) based methods, and generates real-time trajectories for locomotion on surfaces with uncertain vertical motion. We design an optimization-based torque control law and validate our framework through simulations and hardware experiments. The validation results on hardware demonstrate robust locomotion on surfaces with uncertain and unknown motion, including external disturbances and uneven terrain.

Keywords: Design Optimization in Mechatronics, Aerial Robots
Abstract: Single locomotion robots often struggle to adapt in highly variable or uncertain environments, especially in emergencies. In this paper, a multi-modal deformable robot is introduced that can both fly and drive. Compatibility issues with multi-modal locomotive fusion for this hybrid land-air robot are solved using proposed design conceptions, including power settings, energy selection, and designs of deformable structure. The robot can also automatically transform between land and air modes during 3D planning and tracking. Meanwhile, we proposed a algorithms for evaluation the performance of land-air robots. A series of comparisons and experiments were conducted to demonstrate the robustness and reliability of the proposed structure in complex field environments.

Keywords: Walking Machines, Aerial Robots, Modeling and Design of Mechatonic Systems
Abstract: Robots able to run, fly, and grasp have a high potential to solve a wide scope of tasks and navigate in complex environments. Several mechatronic designs of such robots with adaptive morphologies are emerging. However, the task of landing on an uneven surface, traversing rough terrain, and manipulating objects still presents high challenges.

This paper introduces the design of a novel rotor UAV MorphoGear with morphogenetic gear and includes a description of the robot’s mechanics, electronics, and control architecture, as well as walking behavior and an analysis of experimental results. MorphoGear is able to fly, walk on surfaces with several gaits, and grasp objects with four compatible robotic limbs. Robotic limbs with three degrees of freedom (DoFs) are used by this UAV as pedipulators when walking or flying and as manipulators when performing actions in the environment. We performed a locomotion analysis of the landing gear of the robot. Three types of robot gaits have been developed.

The experimental results revealed low crosstrack error of the most accurate gait (mean of 1.9 cm and max of 5.5 cm) and the ability of the drone to move with a 210 mm step length. Another type of robot gait also showed low crosstrack error (mean of 2.3 cm and max of 6.9 cm). The proposed MorphoGear system can potentially achieve a high scope of tasks in environmental surveying, delivery, and high-altitude operations.

Keywords: Design Optimization in Mechatronics, Unmanned Aerial Vehicles
Abstract: In recent years, unmanned aerial systems (UAS) are being utilized for a variety of increasingly complex tasks, including the inspection of offshore installations and the transportation of medical equipment. This has motivated the development of mission-specific dynamic design procedures. The theory of combined control and design, also known as co-design, extends the traditional approach of design optimization and trajectory optimization by integrating both into a single treatment. This results in coupled solutions that are unattainable through a conventional sequential approach. Studies have demonstrated the effectiveness of combining surrogate-assisted optimization methods, such as Bayesian optimization, with a nested formulation of the co-design problem. In the present work, we extend this approach by simultaneously treating multiple objectives. A reformulation of the Bayesian optimization framework through the use of an alternative acquisition function is fit around a trajectory optimization routine. This results in a novel framework that generates optimized designs that outperform the standard design in various metrics. This allows the designer to select a compromising design based on the system's application type and confirms the effectiveness of the concurrent design and control procedure. The subsequent methodology is evaluated on the mission-specific design of a fixed-wing unmanned aerial system, with the aim of conducting a survey mission in challenging terrain. To model the dynamics of the aircraft, the differential flatness of the system is utilized.

Keywords: Aerial Robots, Unmanned Aerial Vehicles, Mobile Robots
Abstract: The monocopter’s distinctive single-wing design, which mimics an autorotating samara seed, has sparked substantial interest in expanding its versatility for various applications. In this regards, the Ground-Aerial Dual Actuator Monocopter (G-ADAM) – a hybrid multi-modal monocopter capable of transforming from flying to ground movement, and vice versa – addresses the latest trend of transformable robots that can operate in diverse environments. With only two actuators, GADAM can promptly transition between ground mode and aerial mode in just approximately 3 seconds. The motor used for the aerial mode is also utilized as propulsion for the ground mode, while the steering mechanism, controlled by a servo through physical linkages, provides control over the direction of the motor thrust in ground mode. A closed-loop control with manual tuning is applied to enable autonomous operation and position control during aerial and ground missions. Overall, G-ADAM successfully demonstrates the capability to operate and transition between ground and aerial modes.

Keywords: Unmanned Aerial Vehicles, Aerial Robots, Transportation Systems
Abstract: This paper presents the design and development of a Vertical Take-off and Landing (VTOL) fixed-aircraft intended for autonomous missions. It provides an overview of the current state of VTOL technology and its applications. The paper focuses on fixed-wing VTOL aircraft created by Academic Scientific Association High Flyers from the Silesian University of Technology, Poland. The design process and considerations are discussed in detail, including aerodynamics, selection of materials, hardware, control systems and used software. Finally, the paper discusses real-world scenarios that use the designed UAV to solve real-life problems, such as targeted plant protection or the deployment of oral vaccines for wildlife. The authors successfully tested solutions presented in the paper during competitions and real practical applications. Overall, this paper provides a comprehensive look into the design and development of a VTOL aircraft for autonomous missions and presents its effectiveness and capabilities in solving real-life problems.

Keywords: Unmanned Aerial Vehicles, Planning and Navigation, Robot Dynamics and Control
Abstract: This article focuses on investigating the effect of quadrotor's trajectory, especially polynomial trajectories, on its energy consumption. First, model-free expressions for power and energy quotients are introduced to relate quadrotor's power and energy directly to its acceleration. This allows to qualitatively estimate quadrotor's energy consumption and compare the effect of different trajectories on energy consumption of identical or different quadrotors independent of quadrotor's manufacturing specifications. Then, polynomial trajectories are analytically investigated for rest-to-rest 1-D scenarios. Scenarios in 3-D with arbitrary kinematic boundary conditions are analyzed via Monte Carlo Simulations with a sample of 10 000 sets of arbitrary boundary conditions. Polynomial trajectories are compared to energy-minimized trajectories in the literature. The results show that increasing the degree of the polynomial increases quadrotor's energy consumption. Moreover, this article suggests using minimum acceleration trajectories as energy-efficient polynomial trajectories. Finally, the results are validated experimentally.

Keywords: Service Robots
Abstract: We describe the design and prototype development of a soft continuum robotic airbag system, to be deployed from a passive walker. The system can deploy in multiple configurations: to the front, left, or right of the walker depending on the direction of a detected fall. The airbag is inflated in real time using a novel compression system. Results of experiments with the prototype are presented. The system deploys consistently across falls, significantly reducing the g-force of impact.

Keywords: Flexible Manipulators and Structures, Modeling and Design of Mechatonic Systems, Control Application in Mechatronics
Abstract: Existing continuum robots still lack the necessary dexterity and manipulability to inspect and operate in confined space with multiple obstacles. In this paper, we propose a novel hybrid continuum robot (HCR) with enhanced dexterity and manipulability. The proposed 9-degree-of-freedom robot can fit in confined space with multiple obstacles by changing the length of its inner hybrid-structure section and outer flexible section. A rotatable inner hybrid-structure section and an additional distal wrist enable rotation motion and sharp bending at the distal end of the HCR, which enhances its dexterity and manipulability. Besides, we develop a detachable, lightweight (2.5 kg), and compact (41 cm×15 cm×6 cm) actuation system for the HCR. It can be easily integrated with existing commercial robot arms to adjust the pose of the HCR’s base, which further enlarges its workspace. In order to demonstrate the HCR’s obstacle avoidance capability in confined space, a path-planning method is proposed. Simulation results show the dexterity and manipulability of the HCR enhanced by 98 % and 3804 times compared with an existing concentric flexible robot in a confined space with one obstacle. Experiments validate the feasibility of the HCR and its path-planning method.

Keywords: Design Optimization in Mechatronics, Flexible Manipulators and Structures, Modeling and Design of Mechatonic Systems
Abstract: This paper aims to provide a systematic review of the work done on design optimization techniques in the area of compliant and soft robots, with a focus on the manufacturing processes, actuation methods and application areas. The goal of this work is to provide a comprehensive view on recent research efforts using optimization for improving the design paradigms of such robot technologies, combined with insights into the technical and technological trends that could potential steer this area towards widespread adoption in domestic and industrial settings. We have determined that the popular methods of design optimization are topology optimization and generative design. This paper also provides a comprehensive categorization of papers applied to soft and compliant robots.

Keywords: Control Application in Mechatronics, Modeling and Design of Mechatonic Systems, Actuators
Abstract: This article presents an efficient learning-based method to solve the inverse kinematic (IK) problem on soft robots with highly nonlinear deformation. The major challenge of efficiently computing IK for such robots is due to the lack of analytical formulation for either forward or inverse kinematics. To address this challenge, we employ neural networks to learn both the mapping function of forward kinematics and also the Jacobian of this function. As a result, Jacobian-based iteration can be applied to solve the IK problem. A sim-to-real training transfer strategy is conducted to make this approach more practical. We first generate a large number of samples in a simulation environment for learning both the kinematic and the Jacobian networks of a soft robot design. Thereafter, a sim-to-real layer of differentiable neurons is employed to map the results of simulation to the physical hardware, where this sim-to-real layer can be learned from a very limited number of training samples generated on the hardware.

Keywords: Biomechatronics, Legged Robots, Mobile Robots
Abstract: Legged locomotion is a highly promising but under-researched subfield within the field of soft robotics. The compliant limbs of soft-limbed robots offer numerous benefits, including the ability to regulate impacts, tolerate falls, and navigate through tight spaces. These robots have the potential to be used for various applications, such as search and rescue, inspection, surveillance, and more. The state-of-the-art still faces many challenges, including limited degrees of freedom, a lack of diversity in gait trajectories, insufficient limb dexterity, and limited payload capabilities. To address these challenges, we develop a modular soft-limbed robot that can mimic the locomotion of pinnipeds. By using a modular design approach, we aim to create a robot that has improved degrees of freedom, gait trajectory diversity, limb dexterity, and payload capabilities. We derive a complete floating-base kinematic model of the proposed robot and use it to generate and experimentally validate a variety of locomotion gaits. Results show that the proposed robot is capable of replicating these gaits effectively. We compare the locomotion trajectories under different gait parameters against our modeling results to demonstrate the validity of our proposed gait models.

Keywords: Flexible Manipulators and Structures, Medical Robotics/Mechatronics, Space Robotics
Abstract: Tendon-driven continuum robots have drawn interest for a wide variety of applications. Prior work in this area has elucidated the coupled kinematics and statics models that describe the motion and coupling of the robot’s elastic backbone with the driving tendons that are tensioned to change the shape of the robot. However, the full design freedom associated with the routing of the tendon through the supporting “eyelets” in the structure has not been explored. This article describes designs that have multiple tendon paths designed to influence the shape of only one continuously deformable section. It is known that this type of solution generally results in highly coupled tendon kinematics, but we show experimentally that there exist paths for which the tendons are so weakly coupled (kinematically) that they can be locked off to provide configuration-independent stiffening. They could also be displaced independently from one another to control independent deformation modes. The approach reveals a strategy for reducing the uncontrolled compliance of the robot’s body, including the torsional compliance, while retaining simplicity in design and control. In particular, we show that tendons that are routed sinusoidally and helically do not strongly couple to constant-curvature actuating tendons as long as they meet an orthogonality constraint. The added tendons increase the stiffness at the cantilevered end by 4.85x over straight tendons alone without impacting the range of motion in the stiffened condition.

Keywords: Design/control of MEMS-nano devices, Micro-Electro-Mechanical Systems, Control Application in Mechatronics
Abstract: This paper describes a high-bandwidth control system design procedure for a MEMS force sensor equipped with an adjustable stiffness mechanism. When the force sensor comes into contact with a sample that has a stiffness at least comparable to its longitudinal stiffness, the resulting mechanical contact causes the system to become stiffer. This change in stiffness can be seen through the rising resonance frequency and falling dc-gain. In order to maintain closed-loop stability of the system after contact, it is necessary to tune the controller parameters since they are originally designed for the nominal system. By implementing a control system that combines an inner damping loop with a tracking loop together with adaptive algorithms to re-tune the controllers after contact, we were able to obtain satisfactory closed-loop performance. Also, the stiffness adjustment mechanism provides additional means of tuning the system dynamics. The numerical and experimental results demonstrate that these control approaches significantly increase the force tracking bandwidth.

Keywords: Modeling and Design of Mechatonic Systems, Virtual Reality and Human Interface, Technology Enabled Teaching of Mechatronics
Abstract: Atomic force microscope (AFM) is a precision mechatronic system for nanoscale imaging of surfaces. Due to limited instrument access and lack of visualization techniques, understanding its principles can be challenging. Digital twin technology allows the creation of virtual representations of physical systems, which can be particularly useful to address challenges in AFM education. To realistically simulate nanoscale physics, we first developed new efficient algorithms for four virtual scale models, including cantilever mechanics, probe transducers, controller tuning, and contact mechanics. Second, three simulated experiment interactive learning modules are developed for instrument operation, including virtual imaging, system overview, and imaging modalities. In the end, three hardware systems are integrated for an extended reality experience, including a macroscopic AFM scale model, a haptic device for probe-sample interaction force feedback and an upgraded low-cost educational AFM for nanoscale imaging and instrumentation. This completes the eight total modules for the AFM SMILER: A Scale Model Interactive Learning Extended Reality toolkit. Preliminary studies shows the toolkit being helpful for AFM education. In addition to mechatronics and nanotechnology education, techniques developed in this work can be generally applied to computationally efficient realistic digital twin creation.

Keywords: Micro/Nano Manipulation
Abstract: The assembly and arrangement of microfibers have wide applications in biomedicine, material science, and microsystem. However, current micromanipulation methods for positioning and orientating individual microfibers are complex and hard to use. In this paper, we report a novel self-alignment capillary gripper for microfiber manipulation that is facile and convenient. We determine the key parameters of the gripper including the required meniscus volume and the tip aspect ratio of the gripper through both numerical simulation and experimental investigation. A two-stage self-alignment process is employed to achieve high precision. The gripper can pick up and self-align microfibers with an aspect ratio of up to 300:1 at an accuracy of 2.1±2.0 μm and 0.6±0.6 ° or better and create highly parallel linear arrays. The gripper is also versatile, where multiple types of microfibers including glass fibers, carbon fibers, dandelion seed fibers, and cat hairs can be picked up and self-aligned. Additionally, the gripper can construct two-dimensional patterns and plug a fiber into a micro glass capillary.

Keywords: Micro-Electro-Mechanical Systems, Actuators, Control Application in Mechatronics
Abstract: The Atomic Force microscope (AFM) has limited throughput, which is a major obstacle to its widespread industrial application. This is due to the conventional imaging technique where a single AFM probe interacts with each point on a sample sequentially. In this paper, we propose a solution to this problem by introducing an array of three active microcantilevers that can operate in parallel. Although all three microcantilevers can be used for imaging, in this work, we only report imaging with the central microcantilever, while the other two are held at a fixed height above the sample. Each microcantilever has on-chip piezoelectric and electrothermal actuators that provide high-frequency and large-range Z-motion to the tip, respectively. The deflection of the tip during imaging is measured by an on-chip differential piezoelectric sensor, and the topography of the sample is determined by controlling the deflection. We microfabricated the array of microcantilevers and integrated them with an in-house developed AFM set-up to image several calibration gratings. This work lays the foundation for the parallel operation of multiple AFM probes, which can significantly improve the throughput of AFM in industrial applications.

Keywords: Image Processing, Applications of nano technology, Identification and Estimation in Mechatronics
Abstract: This paper presents a data-driven acoustic signal filtering technique to eliminate acoustic-caused distortions in atomic force microscope (AFM) image. AFM measurement is sensitive to external disturbances including acoustic signals, as disturbance to the probe-sample interaction directly results in distortions in the sample images obtained. Although conventional passive noise cancellation has been employed, limitation exists and residual noise still persists. The acoustic dynamics involved, however, is complicated, broadband, and not decaying with frequency increase. Even more challengingly, the acoustic source location being unknown and arbitrary in practice results in the signal to noise ratio (SNR) of the acoustic signal measured becomes low, and the error in the acoustic dynamics measured becomes large, both directly deteriorating the image quality obtained. In this work, we propose a Wiener-filter-based robust filtering technique to improve both the SNR of the acoustic signal measured and the error in the acoustic dynamics obtained. Then a coherence minimization approach is proposed to further enhance accuracy of the filter without modeling via a gradient-based optimization method. Experimental implementation is presented and discussed to illustrate the proposed technique.

Keywords: Micro/Nano Manipulation, Design/control of MEMS-nano devices, Applications of nano technology
Abstract: The automation of highly precise online manipulation of nanoscale and microscale objects is essential for the development of scalable nanomanufacturing with numerous applications. The utilization of global external fields is a widespread technique to control micro- and nanoparticles suspended in fluids. However, this wireless external actuation approach exhibits global and coupled influences in the workspace, hindering robust, independent, and simultaneous control of multiple micro- and nanoparticles. Furthermore, the unpredictable and uncontrolled variations in the structures or compositions of nanowires pose additional difficulties in achieving precise and simultaneous control of multiple particles. Another challenge that remains in the manipulation problem is the constraint on control inputs imposed by the physical limitations of the microfluidic device.

In this paper, an ensemble control system is presented to address these limitations by incorporating the rotational dynamics of nanowires in fluid suspension. Two control methods are proposed: a two-stage open-loop ensemble control law and a model-predictive ensemble control strategy. Simulation results demonstrate that both methods surpass the theoretical limits of simultaneous particle control. Furthermore, the model-predictive ensemble control has the advantage of being able to control more nanowires, not requiring pre-generated trajectories, and having a simpler validation process for control performance during the control process when compared to the open-loop ensemble control.

Keywords: Control Application in Mechatronics, Mechatronics in Manufacturing Processes, Network Robotics
Abstract: This paper introduces a novel decentralized control framework that integrates admittance control, nonsingular terminal sliding mode (NTSM) control, and load distribution to cooperatively manipulate a single object with multiple robotic manipulators. Admittance control grants the system a level of compliance for safe human-robot physical interaction. The admittance controller maintains all communication between the manipulators. The NTSM controller provides accurate tracking of the manipulators in the presence of disturbances and dynamic model uncertainties. A decentralized load distribution method is designed to minimize the internal forces on the object. The proposed framework is applied to numerical simulations of a team of three 3-DOF robotic manipulators to demonstrate its effectiveness in cooperative manipulation tasks.

Keywords: Control Application in Mechatronics, Mechatronics in Manufacturing Processes, Identification and Estimation in Mechatronics
Abstract: Applications of drop-on-demand (DoD) inkjet printing in dosage-matter manufacturing and scalable patterning are attributed to its capacity for producing consistent dosages with high placement accuracy. In practice, with the same drop jetting profile, drop volume and drop jetting velocity are affected by variations in ink properties and environmental conditions. Open-loop calibrations are time-consuming and contribute to frequent line stoppage or unacceptable product variations. In this work, a two-input two-output stochastic drop volume and jetting velocity model is derived based on ink jetting calibration data. A control algorithm using drop-image-based one-step look ahead estimation of process model parameters is developed to regulate drop volume and jetting velocity. Boundedness and convergence of the parameter estimation error and stability of the closed-loop system are provided. Experimental results demonstrate a significant reduction to within 1% relative error in the drop volume and jetting velocity using the proposed control algorithm.

Keywords: Control Application in Mechatronics, Machine Learning, Design Optimization in Mechatronics
Abstract: Field-Oriented Control (FOC) is among the most popular control architectures for brushless BLDC motors, employed in several mechatronic applications. Data-driven strategies allow for model-free, optimal tuning of FOC parameters, optimizing a quantitative performance index. While fast, noniterative data-driven techniques, such as Virtual Reference Feedback Tuning (VRFT), are sensitive to the choice of the training experiment and the desired closed-loop behavior. On the other hand, iterative data-driven techniques represent a more robust approach, with less critical experiment design and the ability to account for the presence of nonlinearities. However, commonly used iterative algorithms, such as Bayesian Optimization (BO), are often computationally expensive, and require caution in the selection of the parameters to avoid instabilities in closed-loop experiments. The contribution of this work is to formulate the tuning problem of FOC parameters as a model reference optimization problem suitable to be solved with Set Membership Global Optimization-Δ. This novel, iterative algorithm allows one for the specification of safety constraints and is computationally more efficient than BO. An extensive experimental analysis on a real setup confirms the effectiveness of the proposed approach, and shows that a safe warm start based on VRFT yields faster convergence to the optimal parameters.

Keywords: Control Application in Mechatronics, Robot Dynamics and Control, Software Design for System Integration
Abstract: Modular systems offer increased system versatility and efficiency. Work-drive systems are a subset of mechatronic systems, often modular, featuring a working function and a driving function. Efficient module changes are a core challenge of modularity as software adaptations are needed to accommodate the various module functionalities, geometries and dynamics. Traditional virtual commissioning reduces the development time of products and systems. Additionally, quality improvements are achieved by virtue of earlier and more thorough testing in a risk-free environment. Specifically, control software developed and tuned using a system’s virtual replica can be deployed to the system with little or no modifications. Current virtual commissioning solutions lack automated capabilities or solely employ kinematic models. The digital twin framework proposed in this paper for automated virtual re-commissioning uses a dynamic multibody model to adapt software during module changes in an operating environment with little to no help from a human operator. The proposed framework is demonstrated in simulation for low-level control loop re-commissioning. A sample task sequence is executed in three test cases: 1) baseline 2) system parameter change 3) low-level controller re-tune. The simulation results show an increase in tracking error in 2) compared to 1), illustrating the need for controller re-tune. This subsequently brings back similar performance as the baseline case, i.e. a decrease of 10% tracking error in 3) compared to 2).

Keywords: Control Application in Mechatronics, Image Processing, Identification and Estimation in Mechatronics
Abstract: Inkjet 3D printing is capable of building high resolution components layer by layer with polymer-based materials that can also include functional components. Currently, most inkjet 3D printers are operated with prescribed layer structures to achieve a desired geometry and, in particular, a desired height profile. This often leads to discrepancy between target geometry and actual products. This article presents a framework to leverage halftoning processes in inkjet printing of images to inkjet 3D printing to improve geometric integrity and specifically a more precise height profile. By using the existing imaging pipeline, this framework requires no modification to current hardware. Halftone is a fundamental step in imaging pipeline for all digital printing systems. Error diffusion is one of the most common and widely used halftone algorithms. In this work, we will use two different error diffusion kernels, the 2×3 Floyd and Steinberg (FS) kernel and the 3×5 Jarvis, Judice and Ninke (JJN) kernel to demonstrate the feasibility and improve height profile control of an inkjet 3D printer using UV curable inks. The current implementation operates in a feedforward manner using a previously validated 2D height profile model to provide heigh estimation after the deposition of each layer. Two 3D geometry samples are printed using the proposed approach. Consistent RMS height profile errors and standard deviations from different samples demonstrated the effectiveness of the proposed approach to improve height profile tracking in inkjet 3D printing.

Keywords: Control Application in Mechatronics, Robot Dynamics and Control
Abstract: This work discusses the use of model predictive control (MPC) for the manipulation of a pusher-slider system. In particular we leverage the differential flatness of the pusher-slider in combination with a B-splines transcription to address the computational demand that is typically associated to real-time implementation of an MPC controller. We demonstrate the flatness based B-spline MPC controller in simulation and compare it to a standard MPC implementation approach using direct multiple shooting. We evaluate the computational advantage of the flatness based MPC empirically and document computational acceleration up to 65%.

Keywords: Modeling and Design of Mechatonic Systems, Identification and Estimation in Mechatronics, Part Feeding and Object Handling 
Abstract: This paper deals with particle motion on a cone-shaped feeder unit of an industrial multihead weigher, that distributes products through rotation. Thereby, rotational speed, rotational direction, and constraint-dependent friction substantially influence particle motion. Thus, particle motion is modeled considering dynamic friction and constraint forces for a viscoelastic case. Due to the cone-shape of the feeder, a specific kinematic model is proposed that comprises a differentiable restriction functions for calculating constraint forces. Afterwards, simulation results are tested against real data for a food application. Furthermore, application cases for the resulting model are proposed: The model can be incorporated into a digital twin environment of the weigher as well as used to generate simulation data for data-driven control algorithms.

Keywords: Modeling and Design of Mechatonic Systems, Novel Industry Applications of Mechatroinics, Control Application in Mechatronics
Abstract: This paper presents a robotic mushroom harvesting solution, consisting of an actuated scanning vision system integrated into a gantry robot. The system is capable of performing segmentation and pose estimation of the mushrooms on dutch shelves commonly used in growing farms worldwide. The vision system employs an active stereo RGB-D camera able to capture a 360° scene of the mushroom bed, providing a high quality reconstruction of the mushroom caps. The YOLOv5 algorithm is used for the detection and size classification of the mushrooms, while a two-step model-fitting method is developed for the pose estimation task. The actuated carriage is compact, designed for operation in real mushroom-growing farms and intended to be used together with a soft gripper. The robot has five actuated degrees of freedom (DoFs), three for the linear motion on the shelves, and two DoFs for achieving the desired orientation for the gripper. In a real harvesting scenario, the robot sequentially scans the selected areas and accurately places the gripper in the appropriate angle of attack utilizing our pose estimation method and the visual servoing module for minor adjustments. The results were promising on all trials using 3D printed white button mushrooms on real soil.

Keywords: Novel Industry Applications of Mechatroinics, Mechatronics in Manufacturing Processes, Intelligent Process Automation
Abstract: In this paper, we propose a robot end-effector for fabric folding along a straight line for garment production. In the garment production process, some of the edges of fabric parts of a garment need to be folded before sewing. A conventional automated folding system has a fixture designed for each shape and size of the folding part. The fixture is not universal. In the case of a pocket setter, for example, a pocket template of the fixture used for folding needs to be redesigned/reconfigured when the shape of the fabric part changes. A conventional automated fabric folding system is designed for the mass production of garments with the same shape and the same size. In this paper, we consider how to perform fabric folding without the use of a fixture, so that the same system could be used for folding fabric parts of different shapes and sizes. We propose a concept of a robot end-effector for fabric folding along a straight fold line and develop a prototype of an end-effector referred to as“F-FOLD” (Free-form FOLDing). Folding of the edge of a fabric part is achieved by moving F-FOLD along the desired straight fold line. Experimental results illustrate how F-FOLD folds a fabric part along a straight line.

Keywords: Robot Dynamics and Control, Novel Industry Applications of Mechatroinics
Abstract: While the disassembly of high-precision electronic devices is a predominantly labor-intensive process, collaborative robots provide a promising solution through human-robot collaboration (HRC). To ensure efficient yet safe collaboration, this paper presents a new way to generate task-constrained and collision-free motion for a collaborative robot operating in a dynamic environment involving human movement, which is traditionally challenging due to the high degree of freedom of the co-robot and the uncertainty nature of human motion. We first establish a neural human-motion prediction model with quantified uncertainty, and then optimize the configuration of the robot online by taking the human motion and uncertainties into consideration. While such rationale is straightforward in nature, our method (1) explicitly quantified the uncertainty of the neural human prediction model to further enhance the collaboration safety, and (2) integrated the quantified uncertainty into the task-satisfied motion planning in real-time to efficiently conduct tasks. Extensive experimental tests and comparison studies have been conducted to validate the efficiency and effectiveness of the proposed planning method.

Keywords: Novel Industry Applications of Mechatroinics, Modeling and Design of Mechatonic Systems
Abstract: Shelling scallops can be a labor-intensive and repetitive task that can lead to musculoskeletal disorders for the operators. The repetitive nature of the task and the force required to open the scallop shells can significant strain the hands, wrists, and arms of the operators. In this study, we explored the automation of the shelling process in the seafood industry. We introduced a new mechatronic system called CoboShell, which automates the opening of scallops and the cutting of the nut muscle using a collaborative robot. CoboShell ensures the preservation of the quality of the fresh sea product. Initially, we addressed a technological challenge by proposing an integrated solution based on the Venturi effect. We used appropriately sized suction cups to handle the non-uniform surfaces of the shells. Subsequently, we focused on a scientific inquiry involving the control of the knife blade's trajectory using a collaborative robotic manipulator (cobot). The goal was to guide a flexible knife blade along the inner flat part of the scallop shell. This process aimed to cut the nut muscle and separate the two parts of the scallop. For that, the entry point of the knife is determined automatically in the centre of the scallop opening using an Artificial Intelligence (AI) based technique. Finally, experimental results as well as the repetitive tests have shown that the cobot provided better quality on the muscle cutting with high accuracy and cadence, comparing to conventional industrial arm in the automation of the scallop shelling process.

Keywords: Medical Robotics/Mechatronics, Modeling and Design of Mechatonic Systems
Abstract: This paper proposes a design of a miniature gripper that can drive a suture needle in Robot-assisted Surgery. The presented gripper has two more advantages over the standard needle driver of da Vinci surgical robot. Firstly, it has a decoupled wrist that allows all joints to rotate independently of each other with no coupling between them. This in turn lets the control strategy to be less complicated since each DOF is actuated by only one motor. Secondly, it has rolling capabilities, similar to the human hand, that allow re-orienting the needle with only two fingers. The gripper is rapid prototyped and tested using a drive unit that is designed and developed in this work specifically for this purpose. Two experiments are conducted to validate the proposed design; in the first experiment the gripper is actuated about the wrist axis while the end effector position is measured and compared with the expected trajectory. The results showed that the wrist is completely decoupled from the other joints, as only a slight variation of 1% was obtained. In the second experiment, the motion capabilities of the gripper are demonstrated, and the rolling functionality is tested in presence of a surgical needle.

Keywords: Virtual Reality and Human Interface, Control Application in Mechatronics, Biomechatronics
Abstract: This paper deals with the design of a new haptic interface to drive a wheelchair locomotion simulator in real-time. The proposed haptic interface considers a reference model of a manual wheelchair (MWC) with a coupled straight line, turn and slope/cross-slope dynamics. This model allows both to reproduce the wheel-ground contact resistances in real-time and to estimate the kinematic motion states of the wheelchair. Then the theoretical concept of the model predictive control (MPC) scheme for linear time-varying (LTV) systems is exploited for the design of the haptic controller in order to handle the reference tracking problem. This controller is based on an LTV model of the MWC system coupled with the ergometer rollers of the simulator using an online identification of its dynamics. This formulation allows us to deal with nonlinearities and variations of the contact friction between the MWC wheels and the simulator rollers. The stability of the simulator haptic interface is demonstrated using the Lyapunov stability tools. Finally, the performance and effectiveness of the proposed haptic interface are evaluated by experimental tests on the PSCHITT-PMR simulator platform using standardized locomotion scenarios.

Keywords: Medical Robotics/Mechatronics, Virtual Reality and Human Interface, Image Processing
Abstract: Virtual fixture (VF) has been playing a vital role in robot-assisted surgeries, such as guiding surgical tools' movement and protecting a beating heart. In orthopedic surgery, preplanned images are often used in the operating room, on which planning curves might be drawn, for instance, to mark out the boundaries for osteophytes to be removed. These curves can be used to generate VF to assist in removing osteophytes during the operation. A challenge is that the hand-drawn curves usually have a random shape and cannot be mathematically represented by equations, thus most of the existing algorithms will not work in this scenario. In this paper, an algorithm of VF generating based on point clouds is presented, with which VF can be generated directly from cloud points, for example, point clouds of hand-drawn curves extracted from an image. The effectiveness of the VF algorithm is evaluated by a series of simulations and experiments. The VF algorithm is also tested in an image-based scenario and its effectiveness is demonstrated. The presented point-based VF algorithm is promising to be used in various applications in image-guided surgery to generate VF for objects with various shapes.

Keywords: Medical Robotics/Mechatronics, Robot Dynamics and Control, Sensors and Sensing Systems
Abstract: Transrectal Ultrasound (TRUS)-guided dual-arm robotic needle insertion system has improved clinical diagnosis treatment for biopsy and brachytherapy. It provides a highly precise and flexible method for inserting surgical needles. In the existing system, both the probe and needle are fixed to the robot's end flange, which prevents the rotation and translation of the TRUS probe and needle from enabling multi-angle scanning and flexible needle insertion. In our previous work, we developed a dual-arm robotic needle insertion system with multi-degree-of-freedom (DOF) end-effectors to address the aforementioned issues. The calibration accuracy of the system directly determines the system's effectiveness. However, existing calibration schemes are challenging to complete the calibration of the dual-arm robotic needle insertion system with multi-DOF end-effectors. Therefore, this paper presents a biplane TRUS probe calibration using dual-arm robotic needle insertion system with multi-DOF end-effectors. In the proposed approach, the kinematic of the multi-DOF probe and needle are first modeled to obtain the calibration parameters. Then the multi-DOF needle and probe are calibrated as the biplane TRUS image, which can be used to track the different motion states of the probe and needle. Finally, the experimental results are obtained and validated on the TRUS-guided dual-arm robotic needle insertion system. The results showed that the calibration accuracy of the overall system is 0.80±0.23 mm, which meets the clinical requirements.

Keywords: Actuators, Medical Robotics/Mechatronics, Identification and Estimation in Mechatronics
Abstract: In orthopedic surgery, making an incision into the spine involves a risk of injury to the spinal cord. In addition, surgeons must determine penetration into the bone using only their haptic senses. This imposes a heavy burden on the surgeon. In this study, an orthopedic haptic drill with a penetration detection scheme based on viscosity estimation is proposed. This drill detects penetration by monitoring changes in the position and force of the linear motor in the drill. The threshold values are automatically optimized according to the estimated viscosity of the object being cut. Therefore, the proposed drill does not require prior setup of the parameters in accordance with the object being cut. The utility of the proposed drill is verified experimentally.

Keywords: Medical Robotics/Mechatronics, Micro/Nano Manipulation, Actuators
Abstract: In this study, a novel magnetic guidance-based drug delivery approach for the inner ear is proposed. The approach incorporates a soft microparticle navigation strategy to promote biocompatibility and mitigate corrosion risks. To avoid damage to the round window membrane, a magnetic diffusion method based on particle chain formation was implemented. This chainlets, once inside the cochlea, form a particle bolus under the presence of a converging magnetic, which was guided within the cochlear canal to the target area. The guidance procedure was controlled through a haptic telemanipulation device. The particle diffusion method through the RWM was tested in an in-silico model as no realistic model to mimic the RWM exists. However, the demonstration of chainlet formation was experimentally achieved. In-vitro evaluations were conducted to demonstrate the feasibility of the proposed method, including the guidance performance of the particle bolus within a human-scale artificial cochlea. These findings lay the foundation for the potential integration of this innovative solution into clinical practice.

Keywords: Actuators in Mechatronic Systems, Robot Dynamics and Control, Flexible Manipulators and Structures
Abstract: Robots with adjustable joint stiffness can ensure safety and manipulation reliability in force-sensitive applications. Existing robots use six-axis force/torque sensors at the end-effector to sense the output force and control the output compliance. External sensors are costly, bulky, and cannot be used to offer active link compliance. To account for link compliance and avoid link collision, robots need to have a torque-controlled actuator at each joint. This paper presents a variable-stiffness robot that employs a torque-controlled actuator at each joint. Unlike existing torque-controlled actuators, the proposed actuator has a compact structure and high output moment rigidity. Only encoders are required to sense and control the output torque to exhibit a wide range of controlled stiffness. The end-effector compliance in each direction can be adjusted by varying the compliance contribution of each joint. Design, modeling, and compliance control of the robot are presented. Experiments of the robot in force-sensitive applications demonstrate the accuracy and stability of end-effector compliance control. It is expected that this variable-stiffness robot can be used to interact safely with humans or the environment.

Keywords: Modeling and Design of Mechatonic Systems, Actuators in Mechatronic Systems, Data Storage Systems
Abstract: The trend in robotics has shifted from collaboration with humans to learning and reproducing human skills, reflecting a growing social demand. In response, it is imperative to consider both hardware and software aspects in the design of robots. On the hardware side, the robot should be equipped with adequate sensors for mimicking human motion and force, and its design should meet necessary requirements such as workspace, degree of freedom, payload capacity, and weight, all of which are contingent upon the intended use of the robot. On the software side, the robot should be equipped with a real-time system and stable control algorithms to ensure safe operation. This paper presents the ExSLeR arm which meets the requirements for human skill learning. The performance of the ExSLeR arm is validated by a set of experiments through motion tracking with heavy payload and compliant interaction control tasks.

Keywords: Design Optimization in Mechatronics, Flexible Manipulators and Structures, Service Robots
Abstract: Demand of a lightweight robot arm for dexterously handling objects or working with low inertia has become a new challenge in robotics. This paper comes up with a novel design of a low-inertia robot arm comprising of 5 degrees of freedom (DOF) with 2 DOF at the wrist, 1 DOF at the elbow, 1 DOF at the shoulder, and 1 DOF at the base. The wrist is driven by a cable system, concurrently, all five motors actuating the robot arm locate near a shoulder center with a counterbalanced design. A novel design of a decoupling mechanism without spring components was proposed to enhance the stability of the wrist during loading heavy load. Experimental outcomes showed that our robot arm can lift 5 kg hooked at a long arm, and the accuracy in operating for the arm and the wrist reached smaller than 1 mm. This design is expected to generate a low-inertia robot arm for safe interactions and mobile applications. Our design targets to reduce the payload ratio to 1:1 with the arm weight being 5 kg and the lifetime durability of at least 6 months.

Keywords: Humanoid Robots, Service Robots, Machine Learning
Abstract: Learning from Demonstration (LfD) is a powerful tool for users to encode information about a task for a robot to perform. LfD has been used with some success in specific types of tasks, however very few implementations consider dynamic features in demonstrations while exploring new environments. The goal of this paper is to propose a novel motion planning algorithm that can incorporate the dynamics of a demonstration and avoid obstacles using learned motion primitives. The method uses a combination of hidden semi-Markov models (HSMM) and neural network controllers to classify and encode motion primitives and their sequences. The encoded motion primitives and their transition probabilities are then used to design a discrete sample space to be utilized by a random tree search algorithm. To evaluate this method, a bartending task that includes important dynamic motions was recorded. The recorded demonstrations were used in this method to create the discrete sample space and generate a trajectory for the task in a new environment. The algorithm was run 100 times with a randomly selected set of obstacles and found a feasible trajectory with 91% success.

Keywords: Control Application in Mechatronics, Robot Dynamics and Control, Software Design for System Integration
Abstract: This paper seeks to understand the viability of encrypted robot control. Controllers are susceptible to malicious attacks unless controller parameters are encrypted; however, homomorphic encryption is necessary in order to allow controller mathematical operations on encrypted text, but is limited due to heavy computational overhead. Encrypted control is accomplished via the implementation of Dyer’s somewhat homomorphic encryption scheme on multi and single threaded matrix transformations in order to telecommunicate movement commands between a virtual-reality joystick and a robot arm. Results find that encrypted teleoperation via the user interface is a viable encrypted controller technique, and is optimally produced on multi-threaded systems.

Keywords: Modeling and Design of Mechatonic Systems, Fixture and Grasping, Flexible Manipulators and Structures
Abstract: The design of a robotic hand incorporating a critical multi-DOF palm depends on studies of the anatomical structure of the human palm model. Shaping of this large grasping region is simplified to depend on arches formed by relative movement of the phalanges and metacarpal. Compliant Anatomic Palmar Mechanism (CAPM) replaces these arches to form an interconnected compliant structure that can be used in grasping to conform to contacting objects to augment stability. FEM is used to simulate the range of intrinsic movement of the palmar surface. Plotting these results determines the kinematic relationship by relating thumb rotation and metacarpal translation to the deformation of the palmar region.

Keywords: Novel Industry Applications of Mechatroinics
Abstract: Aerospace has always been a challenging environment for automation. Long takt times, low volumes, high variation, and requirements for high precision make it challenging to transition laboratory R&D to qualified production automation. Boeing has a decades long history in developing, advancing, and deploying, automation for aerospace production. As we look into the future of production, we see new opportunities to accelerate the development and transition of new automation from R&D to production ready. In this presentation, we share some examples of automation at Boeing, current work in leveraging autonomy and robotics, and opportunities in simulation and virtual commissioning to accelerate development, qualification, and deployment of production ready systems.

Keywords: Aerial Robots, Identification and Estimation in Mechatronics, Sensor Integration, Data Fusion
Abstract: Small aerial vehicles have great potential for applications such as manufacturing, logistics, and wildlife surveys. However, their limited payload capacity and endurance pose significant challenges for onboard sensing and navigation, especially for millimeter- to centimeter-scale flyers. This work offers a sensing and control strategy for a small quadrotor to achieve reactive autonomy, defined as flying and avoiding collisions. This relies on a minimal suite of sensors typically employed for hovering flight only. We analyze and model the aerodynamic interactions between propellers and nearby walls, which are amplified by the robot's ducted propellers. The results are integrated with flight dynamics to enable the robot to estimate wall distance and direction. A flight controller is devised to safely stabilize the robot near a wall. Together, the sensing and control framework allows the robot to react, fly, and avoid collisions without extra sensors or visual-inertial navigation.

Keywords: Unmanned Aerial Vehicles, Robot Dynamics and Control, Actuators
Abstract: In this paper, the problems associated with UAVs and torsional tasks constraints regarding valve turning are addressed. An add-on thrust vectoring device which enhances manipulation options available to a conventional multirotor UAV is developed and described. We further expand this concept, by presenting two design configurations for a thrust vectoring device, which allows a UAV to perform torsional work. A high torque configuration composed of three electric ducted fans allow for a torsional moment to be generated in the z axis. A dual torque configuration composed of two electric ducted fans which allows the torsional moment to be oriented around the frame of the UAV The proposed system expands the aerial manipulation options available to a conventional multirotor UAV, as well as the forces the vehicle can generate. The experimental results illustrate the forces and torques that can be generated independent of the UAV's orientation.

Keywords: Control Application in Mechatronics, Unmanned Aerial Vehicles, Network Robotics
Abstract: In this study, we address the analysis of the collective behavior of a swarm of dynamic agents under the control of a generalized cyclic pursuit (GCP) scheme. The detailed features of this study are as follows. First, the generalized frequency variable (GFV) is used to show how a dynamic multi-agent system, whose collective behavior is guided by the GCP scheme, may be formulated into the LTI system framework. Then, we examine the stability, instability, and marginal stability of the dynamic multi-agent systems under discussion using a graphical framework based on the stability analysis of a general LTI system with GFV. Second, although the suggested graphical analysis framework is highly proficient in anticipating rendezvous or diverging spiral motions of GCP-controlled dynamic multi-agent systems, it may prove challenging to precisely predict whether a group of dynamic agents will move in a circular or spirograph-like fashion. Therefore, an analytical tool is developed to overcome the limitations of the graphical technique. Third, we describe the steady-state formation trajectories of a swarm of GCP controlled dynamic agents by explicitly taking into account their general continuous-time LTI model and the case where there are more than two pairs of closed-loop poles on the imaginary axis of the complex plane. Additionally, we discuss the analytical standards for evaluating the spirograph-like closed and open orbits that correspond with the dynamic agents’ steady-state trajectories. Lastly, the study presents comprehensive simulation results that demonstrate the validity of the developed analytical methodologies.

Keywords: Network Robotics, Planning and Navigation, Robot Dynamics and Control
Abstract: This work presents a new delayed-self-reinforcement (DSR) control approach for human-led multi-robot platooning through an area with obstacles. Recent works have shown that with the use of DSR-based approaches, the velocity cohesion and robustness of the vehicle platooning can be improved. However, it only applies to the 1-dimensional longitudinal control. This work further extends the applications of the DSR-based approach in the 2-dimensional space on a mobile robot network, by combining the DSR approach with the trajectory planning based on Bezier Curve. With the 2-dimensional estimated trajectory of the predecessor projected to the 1-dimensional curve, the DSR approach greatly reduces the tracking error on the 1-dimensional space of the target trajectory. The proposed method only uses the local sensing information of the current and historical steps. Comparative simulation results show that both the longitudinal and lateral tracking errors are reduced by 99% and 85% with the use of DSR approach during transitions, compared to the case using standard dynamical feedback linearization but without the use of DSR.

Keywords: Mobile Robots, Control Application in Mechatronics, Robot Dynamics and Control
Abstract: This paper presents the design and control of a solar panel cleaning mobile robot carried by a drone. The robot has tracked wheels to stick to the slanted solar panels and move. Control between suction pad and wheel velocities has to be done with care in order not to slip down while moving. Experimental studies of moving on the solar panel were demonstrated to confirm the feasibility.

Keywords: Mobile Robots, Sensors and Sensing Systems, Robot Dynamics and Control
Abstract: This work focuses on exploiting the concept of ergodicity for motion planning to effectively guide emergency responders or emergency deployed unmanned autonomous systems (UAS) to search and locate a buried snow-avalanche victim. Statistics show that 90% survival rate occurs when an avalanche victim is located within 15 minutes of being buried. As interest in exploiting UAS for first response increases, effective search algorithms for autonomous robotics can help improve search and rescue. A new motion planning algorithm that utilizes ergodic exploration and information theory is developed where the optimization process considers robot dynamics. As the robot agent explores, sensor measurements are processed by a Bayesian filter for victim localization. Compared to existing similar approaches, the proposed search method systematically maximizes information gain and ensures that search trajectories are dynamically feasible. Simulation results are presented to demonstrate the performance of the algorithm for estimating and localizing a buried snow-avalanche victim.

Keywords: Network Robotics, Part Feeding and Object Handling , Flexible Manipulators and Structures
Abstract: This work presents new control approaches for flexible object transport using robot networks. Recent works have investigated bio-inspired strategies to transport objects using decentralized robot networks that only use local measurements without the need for communication between robots [1], [2]. However, current decentralized theories focus on ensuring state consensus at the end of the transition and not during transition. Deviation of states during transition causes large deformation, which can lead to damage of the object transported. With current methods, deformation can only be reduced by increasing the transport time. In contrast, this work develops a delayed self- reinforcement (DSR) [3] approach for transport tasks to reduce deformation during transport of flexible objects, without increasing transport time. An advantage of the DSR method is that it only uses a delayed self reinforcement of each robot’s actions using prior available data and does not require additional information from the network. Furthermore, experimental results are presented to show that the proposed DSR-based transport method can reduce the deformation by at least 75% for the same transport time, when compared to the case without DSR.

Keywords: Planning and Navigation, Mobile Robots, Service Robots
Abstract: This paper presents a navigation strategy for an autonomous forklift used in automated warehouse. The linear segments parabolic blends-based trajectory planner and model predictive control-based motion controller are designed. The performance of the suggested method is demonstrated via Matlab simulations in a warehouse environment.

Keywords: Planning and Navigation, Robot Dynamics and Control, Mobile Robots
Abstract: This study introduces a dynamic inversion based trajectory planning algorithm for wheeled inverted pendulum (WIP) robots that incorporates a linear joint atop the WIP body. We utilize the singular perturbation technique to obtain an asymptotic series solution for the inverse joint trajectory, while considering kinematic and dynamic constraints.

Keywords: Legged Robots, Robot Dynamics and Control, Control Application in Mechatronics
Abstract: We present Late Breaking Results on achieving robust quadrupedal locomotion by stabilizing a hybrid-linear inverted pendulum (H-LIP) stepping on surfaces with vertical motion. Our framework analyzes H-LIP stability, derives feasible and stable footsteps using quadratic programming (QP) based methods, and generates real-time trajectories for locomotion on surfaces with uncertain vertical motion. We design an optimization-based torque control law and validate our framework through simulations and hardware experiments. The validation results on hardware demonstrate robust locomotion on surfaces with uncertain and unknown motion, including external disturbances and uneven terrain.

Keywords: Unmanned Aerial Vehicles, Control Application in Mechatronics, Aerial Robots
Abstract: This paper studies formation control problems for leader-follower multi-quadrotor systems subject to unknown perturbations and limited resources via an event-triggered mechanism. A distributed adaptive dynamic event-triggered formation control (ADETFC) protocol is designed by utilizing a sliding-mode control (SMC) approach, such that the integral sliding-mode manifold can be reached in finite time for the states of the nonlinear, coupled and underactuated system with unknown external disturbances. A distributed integral sliding-mode surface is proposed to guarantee the formation performance as the state trajectories of multi-quadrotor systems move on the constructed sliding manifold. Then, a novel adaptive dynamic triggering strategy is developed to adjust the triggering interval dynamically, and thus reduce the unnecessary resource consumption. Via the Lyapunov stability theory and Barbalat lemma, sufficient conditions to ensure the formation results are derived for leader-follower multi-quadrotor systems. Experiments to validate the effectiveness of the proposed control scheme are conducted.

Keywords: Control Application in Mechatronics, Unmanned Aerial Vehicles
Abstract: Research and development are active in multirotor drones. Attention has been focused on improving drone mobility performance by introducing variable pitch propellers. However, previous studies have not considered main motor currents in their controller design. The aim of this study is to improve thrust response by controlling the variable pitch propeller in the thrust dimension while keeping steady-state efficiency. feed-forward control of thrust by switching modes using maximum current was designed. The control is designed to switch between a thrust reaching mode that uses pitch angle and rotational speed and a efficiency optimizing mode. The mode switching transitions were verified by simulation, and the effectiveness of the proposal was experimentally validated.

Keywords: Unmanned Aerial Vehicles, Robot Dynamics and Control
Abstract: This paper presents a quasi-static state feedback (QSF) for motion control of a Slung Load System (SLS) which is a flat system consisting of a multirotor drone and suspended payload. The design exactly linearizes the closed-loop in new state coordinates. The linearizing feedback has an important static dependence on state and does not require a dynamic controller. After linearization, a straightforward output tracking control ensures that error dynamics in the design coordinates is linear and exponentially stable. The control design compensates for rotor drag and is validated in an open-source PX4 Software-in-the-Loop (SITL) simulation.

Keywords: Unmanned Aerial Vehicles, Robot Dynamics and Control
Abstract: A slung load system (SLS) is a mechanical dynamical system composed of an unmanned aerial vehicle (UAV) carrying a slung load. The nonlinear underactuated SLS dynamics make its motion control a challenging and current problem. This paper proposes a motion control that uses path-following instead of traditional trajectory-tracking. The method defines a geometric path in 3D space for the SLS to follow and renders it controlled-invariant. Output tracking error dynamics are exponentially stabilized using a dynamic state feedback linearization. Simulations demonstrate the robustness of the control to payload mass uncertainty and its benefits over trajectory-tracking.

Keywords: Aerial Robots, Unmanned Aerial Vehicles, Control Application in Mechatronics
Abstract: The development in the design and control of aerial actuated monowing rotorcrafts (commonly known as monocopters) has grown steadily in the past decade. To date, multiple forms of it are being produced from extensive research, however, one area that remains unexplored in this research field is the extent of how we can utilize or exploit these aerial crafts for flights. Thus, the purpose of this paper is to present and demonstrate the conception, design, and control of a new actuated monowing rotorcraft (SICARO) that is capable of rotating in different directions to fly on either side of the wing faced up in a steady and stable manner. Besides going through the research in the methodology for both the design and control of this new platform, this paper also presents results in simulation that are transferred to real experiments for comparison. To validate the effectiveness of the SICARO, the craft is flown on both sides of the wing autonomously where it holds its position in cartesian space. The RMSE for the euclidean distance in the simulations and experiments is below 1m whilst maintaining a stable body attitude.

Keywords: Unmanned Aerial Vehicles, Learning and Neural Control in Mechatronics, Aerial Robots
Abstract: Autonomous helicopter aerial refueling is a challenging problem because of the complex aerodynamic interactions between the helicopter, the tanker and the refueling hose-drogue system. Methodologies solely relying on model-based control approaches are unable to directly address the aerodynamic interactions, whereas pure data-driven methods such as reinforcement learning (RL) often do not provide safety guarantees. Therefore, in this paper, we propose a novel residual RL control methodology that works in conjunction with a model-based outer-loop position controller. Further, we incorporate a safe RL algorithm that assures probabilistic safety guarantees by imposing appropriate constraints. This algorithm leverages the primal-dual formulation of a constrained optimal control problem to solve a sequence of RL problems that ultimately guarantees a probabilistic safety assurance requirement. The RL agent is trained in a simulation platform that consists of a reduced-order helicopter model and a state-dependent control mixer that appropriately delegates the control authority between the outer-loop controller and the RL controller. Once trained, the RL agent is deployed on a physics-based high-fidelity helicopter model without additional parameter tuning. These high-fidelity simulations reveal that the application of the proposed methodology yields a mean 2-norm error of 0.25m at the time of docking, which outperforms a purely model-based controller by 24%.

Keywords: Legged Robots, Robot Dynamics and Control, Walking Machines
Abstract: Low-friction ground conditions present a navigation challenge for bipedal robotic locomotion. While robots might traverse slippery surfaces by carefully planning trajectories, balance recovery from unexpected slip remains a challenge. We present a motion and gait control design for bipedal robotic walkers under foot slip. Slipping dynamics are explicitly considered as a part of the walker's dynamic model. A two-mass inverted pendulum model is presented to capture the ankle actuation effect and used to determine the gait recovery stepping location. A whole-body balance controller is then applied to realize the stepping task. The integration of the abstracted inverted pendulum model and the multi-link model helps build a whole-body operational space design to compute the controlled joint torques. We design a 5-link planar walking robot and implement the control system on the platform. A comprehensive set of walking experiments are presented, demonstrating the performance of the controller for walking on both high-, low- and extremely low-friction ground surfaces. The experimental results confirm that explicit consideration of foot slip improves the performance and yields a stable gait on a low-friction ground surface.

Keywords: Legged Robots, Robot Dynamics and Control, Humanoid Robots
Abstract: Trajectory optimization techniques to control biped walkers are becoming popular with improvements in available solvers. However, many of the proposed controllers assume that the terrain is flat, causing the biped robot to easily fall when the assumption doesn't hold. Humans can easily walk on rough terrain and there are a number of controllers that deal with this issue through perception or sensing but necessary research to tackle this issue without perception/sensing is still lacking. If the walking controller can deal with terrain changes without perception/sensing (terrain-blind), this would ease the computational burden on the controller and decrease the problems caused by errors in perception. This paper proposes a controller that can track the optimized trajectories while handling moderate changes in terrain height. This was mainly achieved by our phase variable manipulation and utilization of a second optimized trajectory that lands the robot safely. We have also improved the robustness of the robot mechanically, by adding passive biarticular muscles. Furthermore, we investigated the effect of biarticular muscle parameters on robustness. Through simulation studies, we show that our proposed controller with proper biarticular muscle parameters can have a 5-link underactuated robot walk without falling on terrains with up to 6.47 cm height changes.

Keywords: Legged Robots, Mobile Robots, Robot Dynamics and Control
Abstract: To realize a wide range of functions in a complex environment, it is necessary to transition between various motions suited to each environment. This article presents a transformable hexapod robot, RHex-T3, which is capable of switching to leg, wheel and RHex mobile modes to improve its flexibility, and climbing the ladders with the Hook-mode. The mechanical design and the implementation of the RHex-T3 are introduced, especially the coaxial transmission mechanism and the innovative 2-degree-of-freedom transformable leg. As the result, experiments are conducted to demonstrate the feasibility and successful performance of the proposed coaxial transformable mechanism. The locomotion performance under three basic mobile modes is evaluated through a series of indoor and outdoor experiments. Furthermore, the ladder climbing function is also verified and its boundary conditions are discussed.

Keywords: Legged Robots, Space Robotics, Vehicles and Space Exploration
Abstract: Interplanetary exploration is at its prime since space transportation technology has become more convenient than ever. Our moon is the primary candidate to become the first extraterrestrial base of space flight operations in the future. The rocker bogie wheel design has been the standard design of locomotion modality for exploration rovers. It could navigate lunar regolith terrain but does not perform well on steep slopes and has the tendency to get permanently stuck on granular media. Alternatively, a legged rover design which contains more degree of freedom joints could free itself when become stuck and could navigate slopes more safely. This paper contains the process of designing and experimenting on an alternative locomotion modality for lunar regolith which could adapt to navigate up and down sloped terrains. In addition, the design would also allow for transformation into roll mode to travel downhill which would optimize energy consumption throughout different types of encountered terrains.

Keywords: Legged Robots, Mobile Robots, Robot Dynamics and Control
Abstract: This study focuses on the wheel-to-leg transformation strategy of a leg-wheel transformable robot. The leg-wheel robot capable of fast transformation by 11-linkage mechanism has a leg length 3.4 times longer than its wheel radius. Because the robot in legged mode has fixed relative phases among the legs for locomotion, while the robot in wheeled mode has random phases owing to wheel steering, the transformation takes into account phase regulation. The transformation of a single leg-wheel is designed to minimize energy consumption to enable it to lift its body. The coordination of the leg-wheels during transformation is designed to maintain stability and prevent leg slippage in kinematic constraint. The proposed strategy was simulated and experimentally validated, and the results confirm its functionality.

Keywords: Legged Robots, Robot Dynamics and Control, Control Application in Mechatronics
Abstract: —In this study, a hybrid impedance and admittance control strategy is developed as a low-level, high-speed controller for legged robots that fuses two controllers within the range of several ticks of a control loop. This strategy enables the rigid-link legs not only to have accurate motion trajectories but also to adapt to the impacts caused by interactions with unknown environments. In addition, owing to the significantly different characteristics of the leg in compression and in tension, the study introduces a novel switching strategy that adjusts the hybrid level of the controller in the range of the leg stride. The proposed strategy was experimentally validated on a linkage-based leg wheel, and the results confirm the effectiveness of the strategy.

Keywords: Genetic Algorithms, Compuational Models and Methods, Neural Networks
Abstract: This paper investigates the tracking control problem of an unstable wave equation with boundary uncertainties. The wave equation under consideration has a negative damper (unstable) at the uncontrolled boundary and uncertain nonlinear dynamics at the controlled boundary. A novel boundary tracking control scheme is proposed by incorporating the backstepping method with adaptive neural networks (NN). Specifically, an adaptive radial basis function (RBF) NN model is first developed to approximate/counteract the system uncertainties. A boundary feedback observer is then designed with such a NN model to estimate the overall state of the wave equation. Based on this, a boundary tracking controller is finally proposed using the adaptive backstepping technique. Uniquely, this new control scheme is capable of rendering stable state tracking (i.e., driving the system’s holistic state to track a prescribed reference trajectory), significantly advancing the current literature that is largely focused on output tracking control. Rigorous analysis is performed to verify the well-posedness and stability of the overall closed-loop system. Simulation studies have been conducted to demonstrate effectiveness of the proposed results.

Keywords: Control Application in Mechatronics, Robot Dynamics and Control, Identification and Estimation in Mechatronics
Abstract: Robust force control systems guarantee robustness to disturbance, including external force. Few previous studies, however, clarify transitions between contact and non-contact. This paper considers an admittance control with the desired relation between force and velocity to achieve safety transitions. Also, the proposed admittance control keeps robust by disturbance observer (DOB). The DOB-based admittance control intrinsically contains robust force control, and a controller during non-contact and one during contact differ only in damping parameter settings. It allows simple contact regulation on transitions. Experiments adopt and validate the proposed method for workspace control of two-degree-of-freedom (2-DOF) manipulators. This paper indicates that the control-based approach, as well as the mechanism-based approach, is one of the effective strategies in human-robot coexisting situations.

Keywords: Modeling and Design of Mechatonic Systems, Design Optimization in Mechatronics, Control Application in Mechatronics
Abstract: Syringe pump has been applied to actuate soft pneumatic robots. Most previous works focus on designs of syringe pump, its applications, and improvement of its problems such as leaking air, inefficient motions, etc. This paper introduces dynamical modeling and parametric analysis of a syringe pump. Syringe pump is made of a commercial syringe and linear actuator. The dynamic equation is derived from the motions of linear actuator, the air dynamics in the syringe, and the air flow inside soft actuator. Because of the high-elastic materials, volume of soft actuator is a time-varying parameter. Therefore, the variation of volume is estimated by the Kalman filter instead of relying on traditional design method. The dynamic model is also utilized to select optimal parameters which are verified by the experiments for the syringe pump. Two system controllers are designed with and without consideration of the pressure dynamics. The controller considering pressure dynamics outperforms. This work shows the benefits of pressure dynamics of syringe pump for both system design and advanced controller design.

Keywords: Control Application in Mechatronics, Robot Dynamics and Control, Unmanned Aerial Vehicles
Abstract: This paper presents a new concept of a predictive controller utilizing future reference trajectory to reduce the delay effect. Time delay critically affects mechatronics systems, and it is still a remaining issue that must be solved. However, existing controllers have a limitation of input type as a constant desired trajectory, and it may limit implementation into various applications. The controller in the paper overcomes the limitation and is capable of tracking time-varying trajectories. The simulation results show that the controller can be applied to more general trajectories for practical applications.

Keywords: Learning and Neural Control in Mechatronics, Control Application in Mechatronics
Abstract: Feedforward control of hydraulic systems is a huge benefit to their performance and has been a research topic for many years focusing on the differential equations of the pump in order to implement pressure control or flow control laws. Considering a servo-hydraulic system which is acutated by an operator, it is inevitable to firstly calculate the required flow to obtain a desired system behavior. A good measure for a suitable pump flow regarding a given input signal by an operator is the resulting pressure drop across the actuated valve. In this paper an adaptive feedforward controller is developed using a gaussian process and a recursive least squares algorithm to calculate the needed flow more accurately resulting in a desired pressure drop repeatedly. The results are then implemented to the hydraulic system and the tracking behavior of the real system is evaluated. This is done using setpoint changes of the operator input. The measurement results for the dynamic actuation of a cylinder are shown and a comparison between the gaussian process and the recursive least squares algorithm is made. With the adaptive feedforward controller the pressure drop can be set more precisely allowing an efficient operation of the overall hydraulic system.

Keywords: Control Application in Mechatronics, Vehicle Control, Modeling and Design of Mechatonic Systems
Abstract: Machines that use a telescoping boom with an attached jib to raise loads to great heights have deadly tip-over hazards. To keep machines safely away from tip-over conditions, machine producers provide a variety of countermeasures, such as outriggers that increase the width of the stability base, counterweights, configuration sensors, control input smoothing, and control computers that stop the machines from moving out of the stable envelope of reachable positions. The computers are programmed to have a stability margin that restricts machine motion well within the envelope of actual stability. These stability margins are set by industry standards that limit the allowable payload weight. However, margins created by payload limits do not provide good margins for other machine parameter variations and configuration errors. This paper calculates stability margins that are not considered by industry standards. The results indicate that these neglected stability margins can be both small and inconsistent throughout the reachable workspace. Therefore, telescoping-boom machines with attached jibs pose safety hazards that are neither well understood, nor adequately addressed by industry standards.

Keywords: Modeling and Design of Mechatonic Systems, Actuators in Mechatronic Systems, Compuational Models and Methods
Abstract: Rotary to translational transmission systems play an important role in many applications from engineering to human assistance devices. Although leadscrews and ball-screws are widely available, they suffer mechanical wear/tear problems due to contact friction. Motivated by increasing demands for energy-efficient mechanisms for mobile and wearable robotic systems, this paper presents an analytical method to design a magnetic-leadscrew (MLS) with embedded sensing. MLS is driven by permanent magnets converting magnetic energy to thrust forces while transmitting the rotary-to-translation motion. However, existing designs generally assume an infinitely long MLS, so its magnetic field distribution is axisymmetric and periodic. To relax these assumptions for applications that require maintaining a constant lead over a short travel, the paper formulates the magnetic field and radial/thrust forces of an MLS in closed form using a distributed current source (DCS) method for developing MLS with an embedded field-based sensing system. The sensing method determines the unique solution to the inverse magnetic field model and measures the translation and rotation independently. With the DCS models, a parametric study has been conducted numerically leading to the development of a prototype MLS with embedded sensing, upon which the magnetic field model, sensing system, and algorithm are numerically illustrated and experimentally validated.

Keywords: Robot Dynamics and Control, Novel Industry Applications of Mechatroinics
Abstract: While the disassembly of high-precision electronic devices is a predominantly labor-intensive process, collaborative robots provide a promising solution through human-robot collaboration (HRC). To ensure efficient yet safe collaboration, this paper presents a new way to generate task-constrained and collision-free motion for a collaborative robot operating in a dynamic environment involving human movement, which is traditionally challenging due to the high degree of freedom of the co-robot and the uncertainty nature of human motion. We first establish a neural human-motion prediction model with quantified uncertainty, and then optimize the configuration of the robot online by taking the human motion and uncertainties into consideration. While such rationale is straightforward in nature, our method (1) explicitly quantified the uncertainty of the neural human prediction model to further enhance the collaboration safety, and (2) integrated the quantified uncertainty into the task-satisfied motion planning in real-time to efficiently conduct tasks. Extensive experimental tests and comparison studies have been conducted to validate the efficiency and effectiveness of the proposed planning method.

Keywords: Compuational Models and Methods, Neural Networks, Robot Dynamics and Control
Abstract: The soft robotics field as a new generation of robotics has become a more popular research field among scientists and engineers. Due to their soft body and flexible structures, soft robots are more capable of addressing real-world tasks in different areas such as medical applications. For this, modeling and control of soft robots are critical because of human interaction applications which cannot be addressed by rigid body counterparts. Using soft materials, different shapes and actuators have made it more difficult for modeling. Additionally, detecting faults in such robots demands more accurate and precise modeling of them. In this paper, a novel machine learning method called deterministic learning is used for training the model of a soft robot with a radial basis function neural network. Then, the fault detection (FD) process is investigated by implementing four different faults. These faults would degrade system control performance, such as decreasing tracking accuracy or even leading the system into an unstable manner. Then, identifying fault occurrence during soft robot operation is studied.

Keywords: Intelligent Sensors, Sensors and Sensing Systems, Artificial Intelligence in Mechatronics
Abstract: In this paper, we present a novel tactile-based slippage-detection method for robotics applications, utilizing a single piezoelectric sensor. The method combines spectral analysis (FFT) and deep learning (GRU) for improved efficiency and adaptability. We implement an automated data-collection process with accurate and unbiased labels of slip events. The proposed method was evaluated through an ablation study, to characterize the influence of different parameters. The results showed a high classification accuracy of 98.70% at 100Hz and detection delays of 8.5 ± 23.7ms, demonstrating the relevance of our spectro-temporal pipeline. The proposed method has the potential to enhance the performance of robotic systems and increase their reliability in robotic grasping applications.

Keywords: Aerial Robots, Unmanned Aerial Vehicles, Mobile Robots
Abstract: With its distinctive single-wing design that mimics an autorotating samara seed, the monocopter has gained substantial interest to expand its versatility for various applications. In this aspect, the Ground-Aerial Dual Actuator Monocopter (G-ADAM) – a hybrid multi-modal monocopter capable of transforming from flying to moving on the ground, and vice versa – addresses the latest trend of transforming robots to operate in diverse environments. With just two actuators, G-ADAM has shown the capability to promptly transition between ground mode and aerial mode, which only takes approximately 3s. The motor used in the aerial mode is also utilized as propulsion for the ground mode while the steering mechanism, which is controlled by a servo via physical linkages, provides control over the direction of the motor thrust in ground mode. A closed loop control with manual tuning is applied to allow autonomous operation and position control during aerial and ground missions. Overall, G-ADAM successfully demonstrates the operation and transition between ground and aerial modes.

Keywords: Rehabilitation Robots, Biomechatronics, Modeling and Design of Mechatonic Systems
Abstract: Lateral resistance walk exercise (LRWE) is a popular method for fitness and rehabilitation training. However, current methods such as lateral band walks (LBW) cannot actively control the resistance training intensity. In this work, we proposed a novel hip exoskeleton which can strengthen hip adductors by applying active resistance torque during lateral walking. The spatial linkage mechanism of the hip exoskeleton was designed and a prototype was fabricated. The dynamic model of transmission system coupling exoskeleton and human body was established. The Proportional-integral-differential (PID) control strategy based on fuzzy tuning was presented to control the resistance torque. Physical prototype experiments showed that the fuzzy tuning PID control strategy could significantly improve the torque tracking accuracy compared to the traditional PID control strategy. The muscle activities of No-exo, Exo-off, LBW, and Exo-on (10Nm, 15Nm, 20Nm) conditions were evaluated on ten healthy male subjects walking laterally at a speed of one step per second. The muscle activities of gluteus medius increased by 51.4%, 413.5%, 591.9%, 721.6% and 918.9% under Exo-off, LBW, and Exo-on (10Nm, 15Nm, 20Nm) conditions, respectively. The corresponding increments for tensor fasciae latae were 52.6%, 1136.8%, 1626.3%, 1994.7% and 2331.6%, respectively. The results demonstrate that the proposed hip exoskeleton can apply to LRWE and improve muscle activities of hip adductors. It will upgrade the exercise method of LRWE and has good potential in strengthening hip abductors.

Keywords: Rehabilitation Robots, Medical Robotics/Mechatronics
Abstract: This paper proposes a portable Unilateral Elbow Forearm Exoskeleton (UEFE) for assisting chronic stroke patients in the activities of daily living (ADL). UEFE provides users 2DoFs assistance: elbow flexion/extension (eF/E) and forearm pronation/supination (eR). Other than eF/E, forearm rotation is equally crucial for completing ADL tasks; however, limited exoskeletons provide eR assistance for users in ADL. Even though some existing exoskeletons are equipped with eR joints, those devices are not practical to use in ADL due to their heavy weight, insufficient assistance, and obstructing handles. In UEFE, both active joints are actuated by Series Elastic Actuators (SEA) through Bowden cables to ensure safe interactions and a lightweight solution. The design of UEFE is based on the ADL requirements, which include the range of motion (ROM) and torque. The handle-free feature also allows users to pick up objects in ADL. A pill-taking task with impedance control demonstrates the feasibility of using the UEFE in ADL assistance.

Keywords: Biomechatronics, Human -Machine Interfaces, Actuators in Mechatronic Systems
Abstract: The field of wearable robotics has made significant progress toward augmenting human functions from multi-modal ambulation to manual lifting tasks. However, most of these systems are designed to be task-specific and only experimentally demonstrate benefits in a single type of movement (e.g. ambulation). In this work, we design, fabricate, and characterize a versatile hip exoskeleton for lifting and ambulation tasks. The exoskeleton is actuated with custom-built quasi-direct drive actuators. We produce an orthotic interface to transmit high torques and assemble a custom mechatronic control system for the exoskeleton. Next, we detail controllers for level ground walking, incline walking, and symmetric knee to waist lifting. Additionally, the actuators’ torque tracking performance is quantified on benchtop and in human experiments. Finally, we validate the efficacy of the system in the tasks of high-speed walking, incline walking, and lifting. During knee-to-waist cyclic lifting, the powered condition exhibited a 16.7% reduction in net metabolic cost compared to the no exoskeleton condition, and a 22.0% reduction compared to the unpowered condition. During incline walking, a 19.4% reduction in net metabolic cost was observed compared to the unpowered condition. Finally, during high-speed walking (1.75 m/s), a 12.5% reduction in net metabolic cost was detected compared to the unpowered condition.

Keywords: Rehabilitation Robots, Parallel Mechanisms, Biomechatronics
Abstract: We present a wearable "exo-shell" device inspired by the human spine for improving the gait of elderly people during obstacle avoidance tasks. This device -- designed and fabricated with origami-inspired techniques -- features a serial chain of lockable joints that can be stiffened using a braking system inspired by laminar jamming concepts. Current related work has identified that the trunk plays a crucial role in obstacle avoidance tasks. In this paper, we thus propose an affordable wearable system that can be quickly fabricated and whose design can be adjusted to fit the individual wearer. The design leverages switchable, passive systems, in combination with lightweight materials that remain as "transparent" to the user as possible when inactive. This paper focuses on translating human requirements into a tangible design that addresses the current state of our biomechanics knowledge. We describe the kinematics and forces of our proposed device, describe the performance of our system in a locked and unlocked state, discuss the integration of various sensors into our device, and characterize the performance of the device when locked and unlocked.

Keywords: Rehabilitation Robots, Medical Robotics/Mechatronics, Flexible Manipulators and Structures
Abstract: Exoskeletons are gaining traction for their use as motion assistive devices for human performance augmentation in occupational settings and rehabilitation in clinical settings. When considering upper body exoskeletons, soft robotic systems are more suitable due to their intrinsic compliance, lighter weight, and lower complexity in comparison to conventional rigid robotics. Regardless of many efforts to make soft robotic exoskeletons for the upper body, current marketed exoskeletons are only focused on the hand, and there is a need for development of this type of device for the wrist. This manuscript reports the design and development of a pneumatically driven wearable wrist exoskeleton made with hyperelastic materials. The exoskeleton is comprised of soft actuators using half-bellow architecture which can create bidirectional motion by applying pressure and vacuum. Two exoskeleton configurations are presented: (1) one actuator on either the dorsal or palmar side of the wrist and (2) two actuators with one on each side of the wrist. Simulation and experimental studies were performed to evaluate the range of motion and torque capabilities of the two configurations. The single actuator configuration produced a range of motion of 45 degrees flexion and 7 degrees extension when the actuator was on the dorsal side. Inverse angles were obtained when the actuator was on the palmar side. These ranges of motion and the torque produced by this configuration demonstrated its potential to assist in object manipulation and load bearing. However, it is still limited in bidirectionality, which may reduce its ability to assist in tasks that require both flexion and extension. The two-actuator configuration produced higher bidirectionality with 45 degrees flexion and 45 degrees extension range of motion, as well as sufficient torque for both directions. Therefore, this configuration has higher potential for assisting tasks in occupational, rehabilitation, and activities of daily living scenarios.

Keywords: Biomechatronics, Rehabilitation Robots, Modeling and Design of Mechatonic Systems
Abstract: Individuals with physical impairments and chronic conditions (including children, adolescents, adults, and seniors) who have motor disabilities are recommended to use assistive devices to perform activities of daily living (ADLs). Developing these devices to be cost-effective, lightweight, and comfortable would make them more practical for home-based usage with a significant impact on people's lives. In this work, a new hip exoskeleton is designed with low weight and cost while ensuring the wearer's comfort in various movements. In addition, this exoskeleton maintains high structural strength and torque power. This lower limb exoskeleton has two degrees of freedom (DOFs) and can generate hip movement trajectories in the sagittal plane. The structure of this exoskeleton was fabricated from light and printable materials such as thermoplastic polyurethane (TPU), Polyethylene terephthalate glycol (PETG), polylactic acid (PLA), and carbon fiber to make it more affordable for a larger population of end-users. A compact control system including a high-torque DC motor, mini-PC, microcontroller, and intermediate boards was carefully selected to optimize the size of this device. Experimental studies have been performed to evaluate the performance of this exoskeleton in walking and sit-to-stand movements at low and high speeds.

Keywords: Flexible Manipulators and Structures, Robot Dynamics and Control, Control Application in Mechatronics
Abstract: The compliant control of a flexible joint relies on accurate external torque information and effective internal disturbance compensation. To achieve this, most of prior works use a built-in torque sensor and a lumped disturbance observer based on a single encoder. This increases the weight and cost of the system. In this paper, a novel dual-disturbance observer (DDOB) based on the encoder feedbacks from both the motor and link sides is proposed, so that the friction and external torque are estimated and compensated separately without the torque sensor. Thereby, a feedforward-feedback-DDOB composite scheme is formed for position control. The modified reference sensitivity of this scheme suggests that better tracking accuracy and disturbance rejection ability are achieved. In addition, the estimated external torque is used to alternate the reference trajectory with the given admittance model. To ensure the feedforward control is realizable, the prediction of the alternated trajectory is done by the online fitting of a polynomial. The output turbulence caused by prediction errors is effectively suppressed by a single dead-beat compensator with the most ancient prediction in memory, while other predictions are weighted by the time-varying ratios. Simulations and real-time experiments are performed to demonstrate the practical appeal of the proposed method.

Keywords: Flexible Manipulators and Structures, Design Optimization in Mechatronics, Modeling and Design of Mechatonic Systems
Abstract: Flexure-joint-based continuum robots are used in a variety of engineering applications, such as minimally invasive surgery and space exploration. However, some highly flexible joints, such as the leaf-spring joint, have a low torsional stiffness, which greatly limits the payload capacity of the constructed continuum robots in their curved configuration. On the other hand, some high-torsional-stiffness joints, such as the cartwheel joint, also suffer from the issue of stress concentration. To cope with these problems, we propose a 3-D-topology-optimization-based method in this article to achieve multi-axis design of flexure joints. Using a multi-objective algorithm, the torsional stiffness and rotational flexibility of different axes of the joint structure are taken into account in the optimization process. In addition, artificial spring elements are introduced in the design problem to realize a balanced stress distribution. To evaluate the feasibility of the proposed method, experiments are also performed to test the bending performance and torsional stiffness of the constructed continuum robot. Results have demonstrated that, the continuum robot equipped with the optimized flexure joints can successfully achieve high torsional stiffness while maintaining its bending flexibility.

Keywords: Flexible Manipulators and Structures, Fixture and Grasping, Part Feeding and Object Handling 
Abstract: Fine assembly tasks such as electrical connector insertion have tight tolerances and sensitive components, limiting the speed and robustness of robot assembly, even when using vision, tactile, or force sensors. Connector insertion is a common industrial task, requiring horizontal alignment errors to be compensated with minimal force, then sufficient force to be brought in the insertion direction. The ability to handle a variety of objects, achieve high-speeds, and handle a wide range in object position variation are also desired. Soft grippers can allow the gripping of parts with variation in surface geometry, but often focus on gripping alone and may not be able to bring the assembly forces required. To achieve high-speed connector insertion, this paper proposes monolithic fingers with structured compliance and form-closure features. A finray-effect gripper is adapted to realize structured (i.e. directional) stiffness that allows high-speed mechanical search, self-alignment in insertion, and sufficient assembly force. The design of the finray ribs and fingertips are investigated, with a final design allowing plug insertion with a tolerance window of up to 7.5 mm at high speed.

Keywords: Flexible Manipulators and Structures, Compuational Models and Methods, Design Optimization in Mechatronics
Abstract: Deformable object manipulation is a challenging research subject that draws a growing interest in the robotic field as new methods to tackle this problem have emerged. So far, most of the proposed approaches in the literature focused solely on shape control. The strain applied to the object is disregarded, thus excluding a large part of industrial applications where fragile products are manipulated, like the demolding of rubber and plastic objects, or the handling of food. These applications require a tradeoff between accuracy and careful manipulation in order to preserve the manipulated object. In this article, we propose an approach to optimally control the deformation of linear and planar deformable objects while also minimizing the deformation energy of the object. First, we modify the framework initially developed for linear soft robot control in order to adapt it to deformable object robotic manipulation. To do so, we reformulate the problem as an optimization problem where the whole shape of the object is taken into account instead of solely focusing on the tip of the object's position and orientation. We then include an energy term in the cost function to find the solution that minimizes the potential elastic energy in the manipulated object while reaching the desired shape. Solutions to problems with high non-linearities are notoriously difficult to find and sensitive to local minima. We define intermediate optimal steps connecting the known initial and final configurations of the object and sequentially solve the problem, thus enhancing the robustness of the algorithm and ensuring the optimality of the solution. %Each solution is then used as input for the next step's problem, therefore enhancing the robustness of the algorithm and ensuring the optimality of the solution. The intermediate optimal configurations are then used to define an end-effector trajectory for the robot to deform the object from an initial to the desired configuration.

Keywords: Flexible Manipulators and Structures, Modeling and Design of Mechatonic Systems
Abstract: Many researchers have been studying long and flexible robots, such as snake-like robots and continuum manipulators. The feature of continuum robots is flexibility; therefore, high rigidity has been considered a characteristic to be avoided or unavoidably accepted for controllability. We envisioned a continuum manipulator that takes advantage of both high rigidity and flexibility to enhance its abilities This paper proposes a concept and an integration method of a new long and flexible manipulator, named Robotic Whip, utilizing both flexible motion and tightening by increasing rigidity. The prototype is 1.4 m in length and 647 g in weight and is actuated by three DC motors rotating winches. Pulling wires enable the device to exhibit an active tightening motion, and loosening wires enable a flexible twining motion. In addition, we estimated the flexible motion of the continuum arm, which consisted of 200 originally designed links, using a simulation based on a rigid links model. Through experiments, it was proven that the prototype performance was adequate, and the device twined around the target bar and enhanced its holding ability by tightening the bar to tow a dolly with a mass of above 2 kg . A comparison of the simulation and actual measurement results showed that our model could reduce the number of prototypes by clarifying the device specifications available for a given situation.

Keywords: Flexible Manipulators and Structures, Parallel Mechanisms, Robot Dynamics and Control
Abstract: This study offers a unique analysis of node-based tensegrity robots guided by pulleys. Tensegrity structures comprise some compressive and tensile members, which provide a lightweight and flexible body. The primary goal of this research is to show how reducing friction in tensegrity robots through the use of pulley-guided nodes can enhance their form-finding capabilities, as demonstrated by experimental evidence. The proposed new pulley-based node design reduces friction between wires and rigid components, thereby improving the form-finding ability of the robots.

Keywords: Automotive Systems, Vehicle Technology, Artificial Intelligence in Mechatronics
Abstract: Vehicle energy consumption model, as a function of its operational environment, plays a significant role in real-time optimization of vehicle route and speed for a given pair of origin and destination with a desired arriving time for the minimal energy consumption. In this paper, a Grey-Box vehicle energy consumption model is developed based on a high fidelity vehicle dynamic model with environmental influence based on the Kriging modeling method, which includes rolling resistance, aerodynamics, gravity and energy consumption of air conditioning and heater (HVAC), along with environmental conditions such as temperature, wind speed, etc. The data-driven model, trained based on Gaussian process assumption, ensures the accuracy of the resulting model with a modeling error below 2.5%. The real-time model updating is based on Recursive Least-Squares (RLS) optimization using current driving data so that the model used for route and speed optimization represents the current vehicle status. The proposed Grey-Box model is validated in Computer-In-the-Loop (CIL) simulations using SUMO and MATLAB with less than 2% error of energy consumption, which is a significant improvement over the vehicle dynamic model with up to 35% error in certain cases. A case study also indicates energy consumption reduction for vehicle route-speed optimization.

Keywords: Control Application in Mechatronics, Learning and Neural Control in Mechatronics, Robot Dynamics and Control
Abstract: The vigorous growth of the electric vehicle in-dustry calls for efficient disassembly of used electric vehicle batteries (EVBs). In the current human-robot hybrid mode, screw disassembly by robots remains a challenge due to the uncertainties in this task. In this paper, we designed an architecture of NeuroSymbolic task and motion planning, which uses neural predicates to map the sensor into a quasi-symbolic state and schedules action primitives autonomously based on current state and goal state. This architecture guarantees autonomy and explainability which is important in human-robot hybrid disassembly pipeline. In primitive implementation, a customized end-effector, accurate vision-based and force-based pose estimation are enabled to ensure the robustness of the system. The experiment shows that the proposed system can achieve 100% success rate in lab environment. We will deploy and evaluate it in the real factory environment in the future.

Keywords: Transportation Systems, Vehicle Control, Control Application in Mechatronics
Abstract: This paper investigates the stability and intervehicle distances (IDs) of heterogeneous platoons under look-ahead topologies and disparity in control gains of position, velocity, and acceleration feedback. When it comes to transient intervehicle spacing, internal stability falls short in guaranteeing a non-colliding distance between vehicles. In other words, having a safe distance between neighboring vehicles requires choosing proper control gains among stable control gains. As such, we formulate the behavior of IDs during platoon travel and find numerically suitable control gains. For formulation, we split the platoon into successive pairs of vehicles and find distance dynamics between neighboring vehicles. Since the platoon is in a look-ahead structure, for the stability of the platoon, we need successive stable distance dynamics. By setting collision and safe distance limits on the formulated IDs, we are set to identify proper control gains for having a non-colliding platoon. Finally, simulation results are provided to illustrate the validity of the theoretical findings.

Keywords: Vehicle Control, Design Optimization in Mechatronics, Compuational Models and Methods
Abstract: Energy management strategies (EMSs) are crucial to the fuel economy of hybrid electric vehicles (HEVs). However, due to the lack of efficient solving approaches, most of existing EMSs mainly focus on the optimal torque split between the internal combustion engine (ICE) and the electric motor but neglect improper ICE on/off switches, and thus usually suffer degraded fuel economy and even unacceptable drivability in practice. To tackle this issue, this paper presents a novel EMS that uses an efficient actor-critic (AC) method to regulate ICE switches with limited computation resources. While common AC methods use complex neural networks (NNs) with arbitrary initialization, the proposed AC uses piecewise cubic polynomials whose parameters are initialized based on optimized solutions of dynamic programming (DP). By this means, the AC can quickly converge with high computation efficiency. The testing results from processor-in-the-loop (PIL) simulations showcase that, compared with a rule-based EMS with tabular value functions, the proposed EMS can greatly improve the equivalent fuel economy by eliminating improper ICE switches after only several iterations of adaptive learning and dramatically save the onboard memory space owing to the concise AC structure.

Keywords: Automotive Systems, Image Processing, Vehicle Control
Abstract: By utilizing the camera installed in the front of a vehicle, this paper proposes on-board camera-based driving force control (CDFC) methods for autonomous electric vehicles driven by in-wheel motors. The image processing algorithm can detect the change in road surface conditions quickly and accurately. This enables the CDFC to update the slip-ratio limiter in real-time. Test results show that the proposed methods can improve traction control performance and reduce inverter input energy.

Keywords: Machine Learning, Automotive Systems, Vehicle Technology
Abstract: The accurate remaining EV range estimation is necessary to overcome the EV users’ range anxiety and infrastructure limitations. However, the traditional methods of EV Remaining Driving Range (RDR) estimation assumes the vehicle speed and energy consumption are consistent with the profiles in the recent history. But in the real world, the driving mode changes rather dynamically according to the user's speed profile, which significantly impacts RDR. Thus, the key question to be addressed in this work is how to accurately predict RDR considering the variation of the user speed profile during the driving trip. So, this work proposed a hybrid deep learning approach for accurate RDR estimation, where the future speed is then updated according to the average speed predicted in a 15-min prediction window. The deep learning approach combines a convolutional neural network (CNN) with Long Short-Term Memory (LSTM) to predict the remaining range of EVs based on historical EV speed data. The proposed CNN-LSTM-hybrid model is trained by exploiting the historical driving data of about 50 users in a two-week test-drive period. The test performance of the proposed EV range estimator is validated using real-world driving data that shows the high accuracy of RDR prediction with an average error of 3.762 km in a testing time window of 7.5 hours. The test results demonstrate the effectiveness of the proposed approach in the EV speed profile prediction, and thus RDR estimation with a high accuracy.