Keywords: Modeling and Design of Mechatonic Systems, Humanoid Robots, Human -Machine Interfaces
Abstract: Differently from active grippers, compliant grippers focus on passive movements using kinematic structures or soft materials, which allows for effective grasping and releasing of objects. The most common gripper configuration consists of two parallel fingers, akin to a crab's claws. Similar to a person picking an object from the floor with their hands, conventional compliant grippers typically undergo four steps to grasp and release objects. The first step is opening two fingers to match the width of objects, by spreading two fingers, it is ready to grasp. And the second step is moving downward. If the object is on the floor, the gripper should move toward it. The third step is closing two fingers, indicating that an object is grasped, and the last one is moving upward for lifting and moving another place. Although these steps are intuitive, controlling them can be complex and time-consuming. To overcome and improve previous disadvantages, the concept of two steps operation and automatic switching is proposed in this paper. Based on armrest and leverage principles, the actions of opening and descending are combined, as are closing and ascending. The armrest principle involves automatic sequential switching based on the same operation, similar to a click pen operation. Thus, when the proposed gripper descends, it makes contact with the object's surface, prompting the fingers to spread out to match objects’ width. Subsequently, as it ascends, it simultaneously grasps and lifts the object. From building concepts and idea, kinematic analysis, spring displacement and grasping force calculations were conducted in this paper. Through simulation and experiments, verifying on various weights and widths of objects were conducted. Consequently, there were three outcomes “grasping only”, “grasping and releasing” and “grasping failure” according with the object width, width and the design parameters.

Keywords: Control Application in Mechatronics, Aerial Robots, Planning and Navigation
Abstract: This study proposes a high-speed FPGA-based flight control unit (FCU) with integrated model predictive control (MPC) for improved real-time flight planning and obstacle avoidance in indoor environment. Initial results demonstrate successful FCU implementation and ongoing experiments to evaluate indoor navigation performance.

Keywords: Mechatronics in Manufacturing Processes, Rapid Prototyping, Hybrid intelligent systems
Abstract: This research presents a hybrid manufacturing machine that combines material extrusion 3D printing with computer-controlled milling processes. The machine is configured in a Cartesian layout and features a scalable modular system for tool exchange. It operates by executing user-generated G-code instructions (macros) to interpret specific actions before and after printing or machining operations. Furthermore, a spline interpolation algorithm is developed to improve kinematic control using a cubic spline interpolator. The modular system allows for easy integration of additional tools like lasers for engraving or cutting, enabling diverse manufacturing processes with simple tool additions and programming adjustments. The above arises from the integration of hybrid manufacturing processes, combining additive and subtractive actions, which is gaining increasing relevance in today's industry. However, it is essential to also bring these technologies into the academic realm, using them as essential tools for rapid prototyping projects. This will enable efficient and versatile 3D printing, CNC machining, and PCB routing on a single machine, fostering innovation and preparing students and researchers for future technological challenges.

Keywords: Identification and Estimation in Mechatronics, Legged Robots, Humanoid Robots
Abstract: This work investigates the robot state estimation problem within a non-inertial environment. The proposed state estimation approach relaxes the common assumption of static ground in the system modeling. The process and measurement models explicitly treat the movement of the non-inertial environments without requiring knowledge of its motion in the inertial frame or relying on GPS or sensing environmental landmarks. Further, the proposed state estimator is formulated as an invariant extended Kalman filter (InEKF) with the deterministic part of its process model obeying the group-affine property, leading to log-linear error dynamics. The observability analysis confirms the robot’s pose (i.e., position and orientation) and velocity relative to the non-inertial environment are observable under the proposed InEKF.

Keywords: Image Processing, Sensor Integration, Data Fusion, Sensors and Sensing Systems
Abstract: Photogrammetry is a technique for 3D reconstruction of target objects from multiple images shot of the object. In the case of actual photography, the object may not be reconstructed due to the inability to shoot images suitable for photogrammetry because of vibration in the camera's angle of view of the object. Therefore, we simulate this vibration by using random numbers and verify the influence of the magnitude of the vibration on the reconstruction result obtained by photogrammetry. The verification results show the relationship between the magnitude of the vibration and the success rate of 3D reconstruction.

Keywords: Legged Robots, Walking Machines
Abstract: Motion planning and control of under-actuated bipedal walking robots involve solving nonlinear differential equations along with discrete events (impacts). The complexity further increases due to motion constraints such as positive ground normal reaction for supporting leg, ground clearance for swinging leg, foot placement constraints etc. One way this complexity has been handled in literature is by employing simple reference models such as those based on Inverted Pendulums or Spring-Loaded Inverted Pendulums (SLIP). These models are computationally tractable but significantly simplify the dynamics of the bipedal walking robots. This work focuses on developing motion planning and control methods based on dynamic models with intermediate complexity that are closer to the actual dynamics of bipedal walking robots, in comparison to SLIP or other inverted pendulum based models. These intermediate complexity models are computationally more tractable than full dynamic models.

In the proposed model, robot links are assumed to have distributed mass and inertia with some special conditions on their center of mass. These models exhibit the property of Differential Flatness, which allows the analytical formulation of a parametrized, dynamically feasible family of trajectories in terms of outputs and their derivatives. Once a family of such trajectories is available, numerical optimization routines can be used to pick a trajectory from this family of trajectories that optimizes specific criteria such as energy consumption and maximum torque requirements while satisfying motion constraints such as positive ground reaction, minimum heel clearance, and no-slip condition. Using the methodology mentioned, a family of dynamically feasible trajectories and energy-optimal trajectories are generated for a five-link biped robot with a torso and a knee joint in each leg. A full-state feedback controller based on DF dynamical structure is shown to eliminate the initial errors in the trajectories. Finally, it is shown through simulation experiments that motion planning and control based on these models as a reference are able to generate walking motion in more general bipedal models that are not differentially flat.

Keywords: Modeling and Design of Mechatonic Systems, Control Application in Mechatronics, Actuators in Mechatronic Systems
Abstract: Magnetic levitation systems with large air gaps and large ranges of motion in all directions can be realized using planar arrays of cylindrical coils, a real time motion tracking system, and feedback control of each degree of freedom in 3D rigid-body motion. These non-contact, frictionless motion systems have potential applications in haptic interfaces, displays, precision manipulation, and medicine. Example systems are shown in Fig. 1. Stable precise control relies on an analytic, numerical, or experimental model of the forces and torques between each magnet and coil with a given current according to their relative position and orientation. At each sensing and control update, the transformation matrix between the coil currents and the total force and torque on the levitated body is calculated, and its pseudoinverse is used to find the optimal set of currents to generate the force and torque for feedback control. This control method relies on principles of linearity and superposition for force and torque generation from coil currents.

When coils with iron cores are used, actuation forces and torques are increased by many times relative to nonferrous cores, but the linearity and superposition assumptions are potentially invalid due to magnetic saturation effects and variations in iron core magnetization produced by other coil currents and magnets in close proximity. The novelty of this work is that we investigate these nonlinear and nonsuperposition effects to find limitations on the coil currents and coil and magnet positions so that standard levitation methods may be used while considering these effects as disturbances. Fig. 2 shows example effects of nonlinearity, where the combination of low magnet heights and low currents produces downward forces due to coil core magnetization from the magnet, and high currents produce saturation effects in generated forces. Worst-case force generation errors due to core magnetization from neighboring coils were found to be less than 5% for coil axis separations greater than 30 mm and coil currents under 2.0 A. Experimental results are shown in Fig. 3 for seven 25x25 mm coils with 8 mm iron cores and 35 mm axis separation and a 19.05x6.35 mm magnet shown in Fig.4.

Keywords: Modeling and Design of Mechatonic Systems, Mobile Robots
Abstract: Recently, robots that deliver goods on behalf of people in urban environments have been widely applied to public. These robots basically perform map-based autonomous navigation and are equipped with local obstacle avoidance functionality. However, there are occasional reports of delivery failures due to obstacles such as curbs and so on. To this end, this study analyzed the mechanical conditions for obstacle overcoming performance to improve the mobility of a wheeled mobile robot and proposed a new driving mechanism that allows step overcoming capability of omnidirectional drive system.

Keywords: Planning and Navigation, Machine Vision, Sensors and Sensing Systems
Abstract: This study introduces a novel mechatronic system that integrates computer vision and dynamic control to optimize lower limb exoskeleton support across various terrains. This work introduces a motorized chest mount camera mount that dynamically adjusts to maintain an optimal field of view (FOV). This setup ensures that terrain features crucial for navigation are continuously centered, achieving an accuracy rate of 83%. Our framework employs an algorithmic suite for terrain classification, step measurement, and staircase detection. Using the YOLOv3 model, it detects ascending stairs with 98.1% accuracy, while an edge detection approach refines descending stair navigation with minimal errors. An integrated Inertial Measurement Unit (IMU) and RGB-D camera precisely capture step lengths, facilitating accurate predictions of the transitional step with 95% accuracy. Furthermore, point cloud analysis is utilized to measure staircase dimensions with a high degree of accuracy, demonstrating an average absolute error of 0.84 cm. This integration of advanced sensing, processing, and control technologies significantly enhances the functionality and adaptability of exoskeletons, paving the way for more effective and versatile assistive devices.

Keywords: Rehabilitation Robots, Actuators in Mechatronic Systems, Biomechatronics
Abstract: In this study, an ankle joint support suit applying shape memory alloy-based fabric-type artificial muscles was introduced. We wear the developed suit and conduct a walking experiment to verify its effectiveness.

Keywords: Robot Dynamics and Control, Vehicles and Space Exploration, Control Application in Mechatronics
Abstract: This poster presents a forward dynamics computation method called ABI for the robotic system with a floating base, such as drone, underwater, and satellite manipulators. The proposed method differs from the conventional ABI [1], in that it can be applied to the robotic system with the floating base.

Keywords: Sensors and Sensing Systems, Human -Machine Interfaces, Machine Learning
Abstract: In the field of robotics, tactile sensors are essential for providing detailed information that visual and other sensors cannot capture. Specifically, tactile sensation includes roughness and cold/warm sensations, which are crucial for object recognition. However, most recent studies focus on either roughness or cold/warm sensations, but not both simultaneously. Here, we propose a flexible tactile sensor using fiber Bragg grating (FBG) sensor to accurately detect both roughness and cold sensations. Our sensor incorporates dual FBG sensing points on a single optical fiber. Also, a temperature regulation system using warm water flow to maintain a sensor surface at body temperature level inspired by human skin temperature regulation through blood flow. Experimental results demonstrate the sensor's high accuracy, achieving 96.00% (std. dev. 8.0%) classification accuracy for cold sensations and 94.00% (std. dev. 8.0%) for roughness detection. This dual-sensing capability enhances the safety and interaction of robots with humans and various objects, contributing to advancements in tactile sensing technology.

Keywords: Transportation Systems, Control Application in Mechatronics, Motion Vibration and Noise Control
Abstract: The capsule train is characterized by driving in a low-pressurized tube and magnetic levitation to reduce air drag and running friction, enabling 1,000 km/h speed. The capsule train being developed by the Korea Railroad Research Institute uses superconducting electrodynamic suspension (SC-EDS) as a magnetic levitation for large levitation gap. However, SC-EDS has the small damping characteristic, which increases vibration, resulting in ride comfort degradation. To control this vibration, active actuators should be applied in secondary suspension of the capsule train. In this study, to investigate the effects of active actuators in laboratory environment, we developed 1/10 reduced-scale vehicle model simulating the dynamic characteristics of the capsule train. Experiments by using developed testbed showed that vibration can be successfully reduced by active actuators with proposed controllers.

Keywords: Transportation Systems, Vehicle Technology, Mobile Robots
Abstract: Individuals with lower-limb disabilities often face significant challenges in overcoming everyday obstacles such as stairs, limiting their mobility and independence. This study introduces the design of a robotic wheelchair engineered to navigate such barriers effectively. The robotic wheelchair not only manages flat terrains but is also equipped with mechanisms that allow it to easily surmount obstacles typically insurmountable by conventional wheelchairs, such as stairs. This capability significantly enhances the mobility and freedom of individuals with lower-limb disabilities.

Keywords: Sensor Integration, Data Fusion, Sensors and Sensing Systems, Intelligent Sensors
Abstract: FMCW radar sensors are crucial for autonomous vehicles, known for their ability to measure depth and cost-effectiveness. However, rain poses a significant challenge to their reliability, especially in detecting targets. Our study seeks to comprehend the influence of rain on FMCW radar performance, with a specific emphasis on assessing its effects and devising strategies for managing them. Rain interferes with radar signals by weakening and scattering them as they travel through the air. This interference makes it difficult for radar to accurately detect targets amidst the background noise created by rain. Additionally, heavier rain worsens the problem by further weakening radar signals. To address the challenges posed by rain on radar sensor performance, this study focuses on developing a model that accurately reflects the impact of rain on the data collected. The approach involves constructing a specialized platform to simulate rain conditions realistically. By conducting experiments on this platform, this study hopes to learn more about how rain affects radar performance under different rain intensities and durations.

By examining the interaction between rain and radar waves, this research seeks to understand how various rain characteristics, including rain intensity and raindrop size, impact radar performance. The radar sensor was housed within this platform, waterproofed to ensure its functionality under rainy conditions. Systematic experiments were conducted, varying the intensity and duration of rainfall, to assess the impact on radar performance. Data was collected under both rainy and clear conditions, allowing for a comparative analysis of radar performance. This experimental setup will elucidate how much radar signals are weakened or scattered by rain. The goal of this study is to not only figure out how rain impacts radar performance but also find ways to make radar more reliable in rainy conditions. By advancing the understanding of how rain affects radar and developing more accurate rain models, this work aims to improve the dependability of autonomous driving technologies in adverse weather conditions.

Keywords: Sensors and Sensing Systems
Abstract: Affordable yet capable and accurate tactile sensors are essential for enhancing the reliability of robot grasping and manipulation in unstructured environments, such as homes. While a wide range of tactile sensors have been developed across literature, integrating them into realistic deployable robots often involves a design tradeoff between expensive, fragile sensors that offer accuracy and more affordable ones with limited functionality. This work bridges this gap by introducing a novel cost-effective tactile sensor (10 per sensor) capable of accurately measuring 3-DOF force vectors (0.4 N RMSE) as well as contact locations (2mm RMSE). Leveraging MEMS barometers along with additional 3D-printed mechanical structures, the sensor exhibits sensitivity to both shear and normal forces and effectively eliminates dead zones. The fabrication process, employing 3D printing and polymer casting, is streamlined, and all associated printed circuit board (PCB) designs and code are made open source, facilitating rapid prototyping for everyone. To showcase its practical applications, the tactile sensor is integrated into a Yale Open Hand, demonstrating its efficacy in realistic manipulation tasks. This work not only presents a viable solution for tactile sensor integration into various robot hands but also offers opportunities for human data collection, thereby paving the way for advancements in tactile sensing across robotics and human-machine interaction.

Keywords: Service Robots
Abstract: This study investigates effective human-robot communication by introducing rewarding and punitive behaviors. The aim is to enhance natural interaction for diverse age groups. This paper focuses on how children interpret the behaviors by designing gestures, eye colors, and voice tones to express these behaviors on the Pepper robot.

Keywords: Service Robots, Mobile Robots, Novel Industry Applications of Mechatroinics
Abstract: Water inlet pipes are critical in hydroelectric plants, but prolonged use leads to wear, requiring thorough inspections to identify potential hazard. To address this, a mobile, modular robot has been developed for manual or semi-autonomous pipe inspections. Equipped with LiDAR, depth sensors, RGB cameras, and IMU, the robot scans pipes for damage and accurately locates itself. Its modular design allows for easy assembly and entry through manholes.

Keywords: Actuators in Mechatronic Systems, Motion Vibration and Noise Control
Abstract: This paper presents a nanopositioner driven by a hybrid reluctance actuator (HRA), where the mover integrates a permanent magnet to generate a bias flux linearizing the actuation force. An advantage of the configuration is that no parasitic force occurs theoretically, unlike conventional HRAs. For validation, the actuation force and the parasitic force are measured by setting the coil current to 0 A and 0.2 A. The results show that the actuation force for positioning significantly varies between 0 N and 54 N, dependent on the mover position. In contrast, the parasitic force varies in a small range between -0.11 N and 1.3 N, successfully demonstrating the effectiveness of the presented nanopositioner. To further investigate the achievable performance of the nanopositioner, cascade control with a position loop and a flux loop is designed for a control bandwidth of 212 Hz, and point-to-point motion of 1 mm is successfully demonstrated with a motion resolution of 4.4 nm at a static point.

Keywords: Modeling and Design of Mechatonic Systems, Actuators in Mechatronic Systems, Actuators
Abstract: The concept of force measurement using zero-compliance mechanism was extended to measurement with cantilever. To achieve the zero-compliance states of the tip of the cantilever (point of action) in measuring force, a three-degree-of-freedom zero-compliance mechanism was developed. It had a triangle whose sides were variable in length. However, the developed device consisted of approximately fifty components, and there were interactions among the motions. For the improvement, another three-degree-of-freedom zero-compliance mechanism is newly designed and manufactured. Because the three motions (two translations and one rotation) of the detection point are quasi-separated, there are less interactions among the motions, which is better for precise measurement. In this article, numerical analyses are carried out predict the displacements and the attitude of the point of action without control and those of the detection point in the zero-compliance states.). In the experiment, static force is applied to the tip of the cantilever. The experimental results demonstrate that the manufactured device operates as expected.

Keywords: Motion Vibration and Noise Control, Sensors and Sensing Systems, Actuators
Abstract: This paper proposes a force balance accelerometer where a hybrid reluctance actuator (HRA) positions a flexure-guided proof mass for acceleration measurement with high sensitivity and reduced noise. The HRA has a coil and a permanent magnet to generate a reluctance force, by which the proof mass can be heavy for high sensitivity. Furthermore, the HRA has an electromagnetic negative stiffness to cancel the flexure's stiffness for noise reduction. For force balance to measure acceleration, a feedback controller is designed, achieving a closed-loop bandwidth of 305 Hz. Experimental results reveal that adjustment of the negative stiffness decreases measurement noise at a low frequency of 1 Hz from 1.3*10^-3 (m/s^2)/Hz^(1/2) to 2.8*10^-4 (m/s^2)/Hz^(1/2) by 77.7% without influencing the sensor's sensitivity, which successfully demonstrates the effectiveness of the proposed accelerometer.

Keywords: Modeling and Design of Mechatonic Systems, Motion Vibration and Noise Control, Actuators
Abstract: This paper presents a comprehensive position uncertainty analysis in a switched current amplifier-driven precision positioning system with an integrated full-state control structure. A mathematical system model is used combining the mechanical, electrical, and magnetical subsystem and their dynamic couplings. Further an internal quantization error feedback in the state-observer of the control is proposed, that reduces the unwanted effect of PWM-quantization on the positioning uncertainty of the system. The presented error budgeting analysis and practical experiments on a built prototype system demonstrate fast reference position tracking and a steady-state positioning uncertainty of 0.6nm (rms), which is an improvement by a factor of 65 as compared to conventional control implementations.

Keywords: Control Application in Mechatronics, Identification and Estimation in Mechatronics, Learning and Neural Control in Mechatronics
Abstract: Pneumatic valves are key components for controlling mass flow rates in general industrial applications. However, they have several nonlinearities such as dead zone and airflow force, making precise control of mass flow rates challenging. Since the poppet position mostly determines the mass flow rate of a valve, this study employs a new valve with an internal position sensor. The authors propose a data-driven feedforward control method to precisely control the poppet position at arbitrary pressure differences by estimating air disturbance force including airflow force. The developed approach compensates for the air disturbance force to the poppet position and enables fast movement without overshooting. The performance improvement is experimentally validated in the poppet position tracking experiments.

Keywords: Control Application in Mechatronics, Identification and Estimation in Mechatronics, Motion Vibration and Noise Control
Abstract: This paper describes a robust controller design method against plant perturbations, based on multiple frequency response data (FRD). The performance of controller design methods based on FRD depends on the reliability of the data. However, this approach has not always been effective for plant whose characteristics are perturbed due to changes in state variables. Therefore, by using multiple FRD that include plant perturbations, we have enabled the design of high precision position controllers that are stable and have high disturbance suppression performance. The measured multiple FRD are integrated into a single FRD based on the gain at each frequency (integrated FRD), reflecting the plant perturbations in the optimization calculations. The effectiveness of the proposed method has been verified through position control experiments using a ball screw whose FRD vary depending on the stage position.

Keywords: Rehabilitation Robots, Human -Machine Interfaces, Biomechatronics
Abstract: Aging is one of the main causes of weakness in mobility and a high risk of falling due to the degradation of neuromuscular and skeletal systems. Tremendous cable-driven robotic assistive devices have been proposed in recent years with the goal of fall risk mitigation and rehabilitation interventions. However, most of them require sophisticated structure and mechatronics design, leading to a relatively bulky nature. In this study, we developed a cable-driven robotic platform for waist perturbation. A lightweight load cell is installed between the end of the cable and a wearable waist belt to measure the pulling force in real time. A closed-loop adaptive full-state feedback control with reference input is proposed to guarantee good torque trajectory tracking performance. Preliminary benchtop and human subject testing with the proposed controller demonstrated an improved force tracking performance of sinusoidal force profiles ranging from 20 N to 80 N, with Root Mean Square Error (RMSE) values of 2.6 N to 10.6 N during fixed-object perturbations and 3.4 N pm 0.2 N to 12.7 N pm 1.0 N during standing perturbations, respectively, as compared to a RMSE of 5.6 N to 21.4 N and 7.1 N pm 0.6 N to 33.7 N pm 2.9 N with the traditional proportional-integral-derivative controller using the same force profile and magnitudes, and under the same perturbation conditions. The hardware and control development of this robotic platform will be used for balance perturbation studies during static standing and human-in-the-loop optimization control studies during dynamic walking tasks.

Keywords: Biomechatronics, Robot Dynamics and Control, Control Application in Mechatronics
Abstract: Passive tumbling uses natural forces like gravity for efficient travel. But without an active means of control, passive tumblers must rely entirely on external forces. Northeastern University's COBRA is a snake robot that can morph into a ring, which employs passive tumbling to traverse down slopes. However, due to its articulated joints, it is also capable of dynamically altering its posture to manipulate the dynamics of the tumbling locomotion for active steering. This paper presents a modelling and control strategy based on collocation optimization for real-time steering of COBRA's tumbling locomotion. We validate our approach using Matlab simulations.

Keywords: Biomechatronics, Rehabilitation Robots, Human -Machine Interfaces
Abstract: Robotic lower limb exoskeletons have been shown to successfully provide joint torques to assist human subjects during walking. Assisting the wearer during gait perturbations to prevent falls still poses a challenge due to specific requirements of the device, and complex bipedal dynamics of recovery. In this study, we present a hip exoskeleton device with pneumatically actuated abduction-adduction motion to provide hip torque for assisting with lateral balance. The device was designed to be wearable, allow integration with previously developed wearable gait perturbation detection system and knee exoskeleton, and produce fast actuation to provide assistive joint torque during gait perturbations. We present the results of the experimental benchtop tests of the device. The maximum torque output and rate of torque development were characterized using a load cell. The maximum angular displacement, with added weights to simulate the leg inertia, was recorded using an inertial measurement unit sensor. Lastly, a preliminary test on a human subject demonstrated that the device, when exerting instantaneous hip abduction torque during swing walking gait, can effectively modify foot placement in the lateral direction. This work contributes towards developing exoskeleton control strategies for assistance during gait perturbations to prevent falls.

Keywords: Biomechatronics, Robot Dynamics and Control, Actuators in Mechatronic Systems
Abstract: Rough terrain locomotion has remained one of the most challenging mobility questions. In 2022, NASA's Innovative Advanced Concepts (NIAC) Program invited US academic institutions to participate NASA's Breakthrough, Innovative & Game-changing (BIG) Idea competition by proposing novel mobility systems that can negotiate extremely rough terrain, lunar bumpy craters. In this competition, Northeastern University won NASA's top Artemis Award award by proposing an articulated robot tumbler called COBRA (Crater Observing Bio-inspired Rolling Articulator). This report briefly explains the underlying principles that made COBRA successful in competing with other concepts ranging from cable-driven to multi-legged designs from six other participating US institutions.

Keywords: Biomechatronics, Human -Machine Interfaces, Rehabilitation Robots
Abstract: Predicting human movements is vital to safely control robots that physically interact with humans. However, predictive neuromuscular models that are fast enough for real-time control applications have proven challenging, due to the complexity of the neural and musculoskeletal systems. Nonlinear optimization-based prediction of movements in a musculoskeletal model is prohibitively slow. On the other hand, highly simplified models based on linear control theory cannot handle complexities of the human musculoskeletal system. Model Predictive Control (MPC) can potentially fill the gap between these two modeling extremes, by taking into account physiological nonlinearities, constraints, and redundancies while keeping computations fast through its receding horizon formulation. This study presents a new predictive model for the human movements based on MPC, which can control activity of four muscles acting on an inertia in a two-dimensional space to generate movements. The MPC results are compared to that of the prominent human motor control model in the neuroscience literature, which is based on linear quadratic regulator. The predicted movements are similar between the two controllers and are qualitatively similar to human behavior. MPC achieves these results while satisfying physiological constraints on muscle activities and ranges of motion – features that are not present in the existing models. These results demonstrate promise and potential for MPC controllers to accurately predict human neuro-muscular activities for the next generation controllers for human-robot interaction.

Keywords: Biomechatronics, Machine Learning, Sensor Integration, Data Fusion
Abstract: Continuous mixing and conveying technology for solid–liquid mixtures is required in the manufacturing process of foods and medicines. To achieve this, we develop a peristaltic mixing conveyor that simulates the function of the human intestines. This device can mix and convey food and medicinal contents by inflating a rubber tube using air pressure. Currently, we are working on a system of content condition estimation using measurement data from the pressure and flow rate sensors installed in the device. However, these measurement methods use air supplied to the device as the measurement target, and the compressibility of air limits the conditions of contents that can be estimated. So, the generalizability of the estimation is low. In this study, a thin pressure-sensitive sensor is installed that can measure the mechanical responses of device contents due to mixing by the device. We also construct a multisensing system that combines conventional pressure/flow rate and pressing force measurements. Sensor data acquired when solid–liquid mixtures are fed into the device are applied to machine learning to distinguish the mixing ratios of the mixtures. Results show that the accuracy of mixing ratio discrimination is improved from 96.7% to 98.9% when pressure and flow rate data are combined with pressing force data. The results thus confirm the improved accuracy of content identification when pressure/flow rate and pressing force measurements are combined.

Keywords: Aerial Robots, Robot Dynamics and Control, Biomechatronics
Abstract: The 3D flight control of a flapping wing robot is a very challenging problem. The robot stabilizes and controls its pose through the aerodynamic forces acting on the wing membrane which has complex dynamics and it is difficult to develop a control method to interact with such a complex system. Bats, in particular, are capable of performing highly agile aerial maneuvers such as tight banking and bounding flight solely using their highly flexible wings. In this work, we develop a control method for a bio-inspired bat robot, the Aerobat, using small low-powered actuators to manipulate the flapping gait and the resulting aerodynamic forces. We implemented a controller based on collocation approach to track a desired roll and perform a banking maneuver to be used in a trajectory tracking controller. This controller is implemented in a simulation to show its performance and feasibility.

Keywords: Biomechatronics, Aerial Robots, Robot Dynamics and Control
Abstract: Vertebrate flyers perform intermittent flights as bounding or oscillating flights for power management. Intermittent flights and the resulting oscillating height during flapping and soaring provide the means of increasing speed without increasing flapping speed. These maneuvers and their robotic biomimicry have remained unexplored so far, which, if understood, can lead to aerial robot designs with endured flight operations. This works attempts to achieve robotic bounding flight using Northeastern's Aerobat platform. Aerobat can dynamically morph its wings by collapsing them rapidly during each gaitcycle. We present a launcher designed that allows bounding flight experimentation of Aerobat in a computer-aided fashion. We augmented Aerobat with a plural tiny thruster to stabilize its unstable roll, pitch, and yaw dynamics. This paper presents our control design based on extending Aerobat's states to accommodate unobservable aerodynamic forces and offers experimental results to support our proposed approach.

Keywords: Aerial Robots, Unmanned Aerial Vehicles, Robot Dynamics and Control
Abstract: As the adoption of Unmanned Aerial Vehicles (UAVs) increases in the industrial sector, the limitations of traditional multirotors have become more noticeable. Though widely employed, conventional multirotors are under-actuated, which restricts the types and quality of manipulation task they can perform. Fully-actuated systems on the other hand, offer an interesting alternative solution with their decoupled forces. However, their widespread use is hindered by complexities in their control and design. Our proposed approach addresses this challenge by introducing multirotors equipped with horizontal thrusters, aiming to find a balance between simplicity and advanced control. These vehicles strategically incorporate additional thrust components tailored to specific tasks, thereby extending the capabilities of traditional under-actuated multirotors. We developed a control algorithm using the PX4 Autopilot to accommodate various flight modes, encompassing directional thrust flight and planar flight. To evaluate our system, we conducted simulations and tested vehicles with different actuator configurations. These simulations were then validated through real-world experiments using a UAV equipped with thrusters and a flight controller running a modified firmware with our control framework. This comprehensive approach allowed us to assess the system's performance in both simulated and practical scenarios

Keywords: Flexible Manipulators and Structures, Aerial Robots, Biomechatronics
Abstract: Robots mimicking the flight of insects and birds (i.e., “flapping flying robots”) have considerably attracted attention owing to their numerous advantages such as energy-saving, reduced noise levels, and safety during a crash. However, the takeoff method leveraged by existing flapping flying robots is limited, as ground-level takeoff may damage the robot. This study aims to develop a remotely controlled flapping flying robot that can fly independently. The developed robot consists of a flapping flying robot that can obtain a thrust of approximately its own weight by flapping its wings and a Snap Motor as a lightweight jumping mechanism. The findings demonstrate that a jumping takeoff effectively avoids wing–ground collision while contributing to stable posture during takeoff.

Keywords: Unmanned Aerial Vehicles, Aerial Robots, Control Application in Mechatronics
Abstract: This paper presents a discrete predictive controller for a class of discrete time-delayed systems. The most time-delayed system, especially a highly unstable unmanned helicopter, has severe difficulties in stability and performance. Furthermore, the presence of disturbance more critically affects the stability of time-delayed systems since the delayed control input may lose the ability to stabilize the state. The proposed controller employs precise prediction of the future state, incorporating exponential stability for predicting future disturbance. In particular, the proposed state prediction can effectively compensate for disturbance effects without any robust control terms. The performance of the proposed controller is validated by numerical simulations. The results can verify the feasibility and performance of the proposed controller in the presence of significant time delay for the unmanned helicopter.

Keywords: Aerial Robots, Robot Dynamics and Control, Planning and Navigation
Abstract: This paper studies the model predictive control problem of quadrotors with external disturbances and measurement noises. A learning-based moving horizon estimation (MHE)-differentiable model predictive control (DMPC) framework is developed. The MHE is designed to provide the estimate of unknown disturbances and system states. With those estimates, the DMPC is developed, and the online learning method for the parameters and cost function dependent on the trajectory are proposed. In this way, the developed framework can adapt to dynamic environment. Furthermore, the MHE-DMPC algorithm with parameter online learning is designed. Finally, the comparison studies are conducted to verify the effectiveness and advantages of the developed method.

Keywords: Actuators
Abstract: We present a soft pneumatic actuator that generates various torsional motions. Attempting to achieve this using conventional design methods resulted in an increase in the number of chambers and piping, which tended to narrow the range of motion. Therefore, we will introduce Helical Coupled Drive as a new design concept that generates a variety of curved shapes with as few chambers as possible. Namely, two helical actuators with variable pitch/phase/length are arranged in parallel so that they mechanically interfere with each other, and by adjusting their parameters. This drive method uses a total of six inputs, consisting of the air pressure of two chambers and the rotational angle of four motors, to create six representative types such as expansion-contraction / C-curve / J-curve / S-curve / helical / spiral. Furthermore, we also present a mechanical model and clarify the design parameters that define its shape. Finally, we verify the effectiveness of the proposed method by having the prototype grab a bottle and pour water into it.

Keywords: Actuators, Actuators in Mechatronic Systems, Design Optimization in Mechatronics
Abstract: Remote actuation is an important design technique to reduce the moving mass of robots for safety. This paper proposes a remote actuator based on the flexible shaft for robot joints. High torque density is achieved at the robot joint, rated at 95 Nm with a low moving mass of 2.6 kg. The design methodology is proposed to develop a remote actuator using a flexible shaft with low-moving mass and torsional compliance at the remote joint with three progressive prototypes. The design of the conduit and link utilized for routing flexible shaft across a joint through the links is analyzed and discussed. A comparison is made with on-joint actuation and potential off-joint actuation using catalog data in terms of torque density, highlighting the potential of remote actuation using a flexible shaft for high payloads at high torque density.

Keywords: Actuators, Actuators in Mechatronic Systems
Abstract: This paper presents a pneumatic actuator utilizing a cylindrical rubber structure achieving an axial elongation of more than 520 % from its original length while maintaining a thin wall thickness and minimal radial expansion of less than 20 %. This study aims to develop an actuator providing a great axial elongation, small radial expansion and thin wall thickness which has a high power-to-weight ratio of pneumatic drive to perform in the narrow spaces. The cylindrical pneumatically driven elongation actuators developed in the other studies include bellows types utilizing material bending property and rubber type utilizing material extension property. These actuators have thick wall thicknesses or expand greatly in the radial direction when driven, and their application environment is limited because they interfered in narrow environments. We develop a cylindrical pneumatically driven elongation actuator compositely restrained by a flexible long yarn and short-oriented fibers that are compatible with rubber. The actuator is structured as a rubber tube helically wound around by the yarn. The actuator deforms in the axial direction and the rubber between one pitch of the helically wrapping yarn expands in the radial direction by air pressure. Then, the rubber is bent, and thrust into the yarn, causing the actuator to break due to stress concentration in the rubber around the yarn. An actuator helically wound around by the yarn many times has a small length of rubber between one pitch of the helically wrapping yarn because the proportion of the thickness of the yarn is dominant in one pitch. Under the above conditions, the deformation rate of the rubber is higher than that of the actuator. Therefore, strong stress acts on the rubber, leading to the actuator breakage. To solve these issues, we develop MD-LUFFY: Massively Deformed Linearly-elongation-actuator Using Flexible Fiber and Yarn that is an actuator reducing the radial expansion of the rubber between one pitch of the helically wrapping yarn to relieve the stress concentration in the rubber around the yarn. MD-LUFFY, a rubber tube compositely reinforced by short-oriented fibers and yarn, can elongate to 520 % within an expansion rate of 20 %.

Keywords: Actuators, Vehicle Technology, Automotive Systems
Abstract: This paper presents a variable flux motor (VFM) with an adjustable rotor-stator mechanism that is designed for electromobility applications. The built-in mechanism allows for the position of the rotor to shift relative to the stator, thereby changing the rotor-stator air-gap magnetic flux. This allows for the electromagnetic characteristics of the motor to change with the operating conditions in a drive cycle. A prototype device is evaluated in an experimental setup to simulate the torque and speed variations expected in a drive cycle. The operation of the VFM with the built-in mechanism is demonstrated, and the efficiency of the motor is evaluated at several critical points of the drive cycle. The results show that an averaged drive cycle efficiency of 92% is achievable which is an almost 6% gain in efficiency over an equivalent fixed flux electric motor applied to the same scenario.

Keywords: Actuators in Mechatronic Systems, Modeling and Design of Mechatonic Systems, Actuators
Abstract: With the increasing popularity of modular robotics, there has been an increasing need for reliable and strong connections between module units. This paper introduces two novel connectors, PAC (Power, Air, Communication) and MagLink (Magnetic Link), designed to advance the interconnectivity of modular robots and actuators. The PAC connector centralizes air, power, and communication in a single housing that simplifies integration and minimizes wiring complexities. Meanwhile, the MagLink connector employs a reversible, low power magnetic locking mechanism, ensuring robust and secure connections between robotic components. Both connectors can be integrated in a single compact unit. We characterized PAC connector in terms of maximum pressure, air flow, and sealing capabilities. MagLink was characterized in terms of connection strength, magnetic field/attractive forces to connect, alignment capture space, and power consumption. MagLink advantages are its low power consumption and 13-fold increase in strength compared to the regular magnetic connection. Together, PAC and MagLink herald a new opportunity in modular robotics, offering high force-to-weight ratio (6.4 N/g), high strength-to-power consumption ratio, reliable electrical connection, and pressure handling capabilities of at least 50 psi (0.34 MPa) packaged in a compact design that can be used across a wide range of robotic configurations. This research presents a step forward toward efficient electro-mechanical-pneumatic connectors for self-reconfigurable modular robots, promising practical solutions for a broad range of modular robotic applications.

Keywords: Actuators, Robot Dynamics and Control, Control Application in Mechatronics
Abstract: Soft robots have become indispensable for safe human-robot interaction in engineering due to their inherent biocompatibility and thus will play a key role in industrial revolution process. However, the poor programming feasibility and motion repeatability of soft robots greatly constrain its applications in industry. In this paper, to address these challenges, we report a novel dragging programming method for precise motion control of a hybrid actuation soft robot. The robot can response the external dragging and be taught to complete various tasks in unstructured environments based on users’ intuitive feedback. Afterwards, the robot can memorize the drag-programmed trajectories and repeat the tasks with high precision (with an average error less than 2% of its body length). Using the dragging programming method, the soft robot has been proven reliable in industrial tasks, such as product quality screening, etc. We envision the proposed dragging programming method and actuation strategy have huge potential for human-soft robot collaborative operations.

Keywords: Machine Learning, Neural Networks, Learning and Neural Control in Mechatronics
Abstract: We present a neural point cloud rendering pipeline through a novel multi-frequency-aware patch adversarial learning framework. The proposed approach aims to improve the rendering realness by minimizing the spectrum discrepancy between real and synthesized images, especially on the high-frequency localized sharpness information which causes image blur visually. Specifically, a patch multi-discriminator scheme is proposed for the adversarial learning, which combines both spectral domain (Fourier Transform and Discrete Wavelet Transform) discriminators as well as the spatial (RGB) domain discriminator to force the generator to capture global and local spectral distributions of the real images. The proposed multi-discriminator scheme not only helps to improve rendering realness, but also enhance the convergence speed and stability of adversarial learning. Moreover, we introduce a noise-resistant voxelisation approach by utilizing both the appearance distance and spatial distance to exclude the spatial outlier points caused by depth noise. Our entire architecture is fully differentiable and can be learned in an end-to-end fashion. Extensive experiments show that our method produces state-of-the-art results for neural point cloud rendering by a significant margin.

Keywords: Machine Learning, Neural Networks, Artificial Intelligence in Mechatronics
Abstract: The behavior in robot-motion learning varies greatly depending on the demonstration data used for learning and modalities of a robot. One of the differences is the emergence of untaught retry behavior. The ability to retry is important for executing difficult and uncertain tasks and improving robustness against external disturbances. We consider it important to recognize the progress status of a task, especially the completion status. We examined cases in which task execution is obstructed in an object-picking task, which is the basic task of many tasks, and demonstrated the effectiveness of two approaches: 1) incorporating a modality capable of accurately recognizing the end state and 2) introducing an action into the demonstration that facilitates the grasping state using existing modalities. The results of experiments using a real robot showed that the tactile modality as approach 1 was effective in recognizing whether the object was grasped and that adding a lifting motion after grasping to visually judge as approach 2 was effective. Upon analyzing the internal state of the recurrent neural network used in the learning model, it was revealed that the two approaches significantly contributed to appropriate state transitions.

Keywords: Compuational Models and Methods, Part Feeding and Object Handling , Machine Learning
Abstract: Advanced hand skills for object manipulation can greatly enhance the physical capability of robots in a variety of applications. Models that can comprehensively and ubiquitously capture semantic information from the demonstration data are essential for robots to learn skills and act autonomously. Compared to object manipulation with firm grasping, nonprehensile manipulation skills can significantly extend the manipulation ability of robots but are also challenging to model. This paper introduces several new modeling techniques for nonprehensile object manipulation and their integration for robot learning and control. Other than a basic map of the object's state transitions, the proposed modeling framework includes a generic object model that can help a learning agent infer manipulations that have not been demonstrated, a contact-based skill model that can semantically describe nonprehensile manipulation skills, and a motion model that can incrementally identify patterns from crowdsourced and constantly collected data. Examples and experiment results are given to explain and validate the proposed methods.

Keywords: Machine Learning, Control Application in Mechatronics, Learning and Neural Control in Mechatronics
Abstract: Human motor control is characterized by its adaptability to new dynamics. As a result of adaptation, humans can achieve motor control with less computational effort while maintaining achievement of the task. In this paper, we hypothesize that such adaptation can be modeled by acquisition process of a feed-forward control sequence. Based on the hypothesis, we propose a state-independent reinforcement learning model of feed-forward control generation and feedback control reduction. A gradual learning strategy is presented on the basis of state-independent and time-dependent reinforcement learning to improve learning efficiency for repetitive tracking control tasks. The proposed motor learning model was validated in simulation of 2-DOF manipulator tracking control task, where the robot could obtain a state-unaware control sequence under unknown dynamics and external force condition.

Keywords: Machine Learning, Novel Industry Applications of Mechatroinics, Identification and Estimation in Mechatronics
Abstract: An accurate modeling approach to predict the trajectory of a drillstring plays a critical role in drilling operation. Nonlinear Delay Differential Equations (DDEs) have been considered as an effective tool to serve the purpose. This paper introduces a novel data-driven approach to model the borehole propagation dynamics by incorporating nonlinear DDEs with Linear Complementarity Problem (LCP) using the Sparse Identification of Nonlinear Dynamics (SINDy) method. The developed model can predict borehole propagation without relying on physics-based information while retaining the same dynamics as those predicted by physics-based nonlinear DDEs. To assess the resilience of the proposed approach, we introduce noise into the dataset, demonstrating the robustness of the SINDy method. Additionally, a stability analysis of the data-driven DDEs offering insights into its reliability and potential applications.

Keywords: Hybrid intelligent systems, Machine Learning, Neural Networks
Abstract: This paper presents a novel approach to address high-dimensional constrained motion planning problems. The proposed method exploits learned latent spaces to efficiently find a feasible constrained path. Although recent data-driven methods have reduced planning time, two major challenges arise as the space dimensionality increases such as in multi-arm manipulation. Firstly, the configuration space search employed by existing data-driven approaches becomes computationally expensive as the complexity of constraints increases. Secondly, preparing datasets for high-dimensional problems is a time-consuming task. To address these challenges, this paper introduces a novel approach: the latent motion method. Instead of exploring the configuration space, the latent motion method explores the latent space with a latent jump method that mitigates topological problems. Additionally, a tangent space dataset augmentation technique is employed to approximate the manifold using a sparse dataset. Experimental evaluations on benchmark problems indicate that the proposed approach outperforms existing methods in high-dimensional constrained motion planning problems.

Keywords: Virtual Reality and Human Interface, Modeling and Design of Mechatonic Systems, Virtual Reality and Display
Abstract: The authors developed an upper-limb-mounted force feedback device using pneumatic artificial muscles and a magnetorheological fluid brake. This force feedback device utilizes a magnetorheological fluid brake and incorporates a mechanism with bevel teeth in the shoulder, providing a wide range of motion. In previous studies, it was confirmed that the device can simulate friction with virtual objects in a virtual reality (VR) space. In this study, the authors conducted force feedback experiments using the developed device in VR content, including linear walking, to examine the influence on motion sickness and immersion. The conditions included the presence or absence of the force feedback device and different methods of movement, such as walking, visual movement, and controller-based movement. Participants were surveyed to evaluate their experiences under these conditions. The results indicated that, concerning motion sickness, the method of movement had a more significant influence than the presence or absence of force feedback. Additionally, for immersion, force feedback, particularly including walking movements, had the greatest potential to enhance the sense of immersion.

Keywords: Modeling and Design of Mechatonic Systems, Actuators in Mechatronic Systems
Abstract: This paper explores the model identification of a novel tendon-driven soft continuum actuator, intended as a functional joint for the social robot HARU. The actuator's design is customized for integration into HARU's eye joints, emphasizing safety in interactions with children, in accordance with UNICEF's "Policy Guidance on AI for Children". The performed experimental study assesses and compares the accuracy of various auto-regressive with exogenous inputs (ARX) modeling techniques—linear, nonlinear, and recursive—through motion data from dynamic experimental tests of the actuator under different orientations. The results provide insights into the efficiency of these modeling strategies in dynamic conditions with continuum actuators, thereby offering a basis for model selection in the integration of soft actuators into robotic systems for practical applications.

Keywords: Modeling and Design of Mechatonic Systems, Actuators in Mechatronic Systems, Biomechatronics
Abstract: This manuscript presents a multiobjective optimization framework for high back drivable partially powered swing assistive actuator knee design. The research exploits a Serial Elastic Actuator (SEA), in parallel with a motor valves controlled hydraulic cylinder, with the purpose of expanding the prosthesis capabilities into the power quadrants of the power plane, without sacrificing the benefits relative to existing microprocessor-controlled-knee prostheses (MPKs), able to allow a strictly-passive ballistic swing-phase. The mechatronic design parameters are optimized by exploiting the multi-objective evolutionary genetic algorithm and validated by means of a knee prosthesis multibody model. The backdrive torque found with the described model corresponds to a relatively low value of 2.56 Nm at the knee joint, allowing the pursued high backdrivability of the system.

Keywords: Modeling and Design of Mechatonic Systems, Actuators, Design Optimization in Mechatronics
Abstract: This paper presents a framework for a low-backlash, high-backdrivable gear based on analytical modeling and simulation. Robot actuators typically combine an electric motor with a high gear ratio gearbox to meet the high torque requirements. The 3K compound planetary gearbox, with its high gear ratio, emerges as a promising candidate for robot actuators used in physically interactive environments due to its high transmission efficiency in both forward and backward motions, thus endowing it with high back-drivability. However, compared to high-ratio gearboxes like harmonic drives, the existing 3K compound planetary gearbox is known to have high backlash. In this sense, the proposed design framework includes: 1) modeling of forward and backward transmission efficiency, 2) derivation of backlash, and 3) maximization of efficiency under bounded backlash constraints. The simulation results indicate that the backlash could be reduced from 24 arcmin to 2 arcmin. We expect that this knowledge could provide insights for designing gears with low backlash and high efficiency for robot actuators used in physically interactive tasks.

Keywords: Modeling and Design of Mechatonic Systems, Human -Machine Interfaces, Parallel Mechanisms
Abstract: In this paper, we present a mechanical upper limbs tracking system designed for manipulation in teleoperation scenarios. In detail, it can track position and orientation of the hand palm. Since it is linked to the Mechanical Hand Tracker (MHT), developed in a previous work, the whole structure can track position and orientation of each fingertip respect to the torso. Such a mechanism can avoid typical limits of alternative tracking methods: occlusions for optical and artificial vision methods, and lack of precision for data gloves. Also, there is no dependence with a grounded, calibrated camera system, thus the wearer can move freely in the space. These features can better fit with certain scenarios such as teleoperation and industrial settings, where reliability of the tracking is of paramount importance. On the other hand, it is challenging to design a multi-dof mechanism that can adapt to different body dimensions, and allowing a large pose workspace. In this work, we propose a methodology to design a linkage mechanism preserving complete upper limbs and fingers mobility. Teleoperation tests assessed the functionality of the developed upper-limbs tracking in a pick-and-place scenario.

Keywords: Modeling and Design of Mechatonic Systems, Applications of nano technology, Actuators in Mechatronic Systems
Abstract: Hybrid reluctance actuators, known for their remarkable motor constant and bidirectional non-contact force, emerge as superior alternatives to piezoelectric stack or voice coil actuators. A key challenge in large-stroke (>1 mm) hybrid reluctance actuators is their inherent nonlinearity characterized by fluctuations in negative stiffness and motor constant. To tackle this problem, we propose a large-stroke reluctance-actuated nanopositioner by leveraging on a compliant stiffness compensator to reduce the adverse impact of the reluctance actuator's nonlinearity. We establish the relationship between the system's equivalent stiffness and the combined effects of the reluctance actuator and compliant compensator. Based on a novel nonlinear decoupling mechanism, the fluctuation in the system's equivalent stiffness is significantly reduced, enabling advanced model-based controls and facilitating high precision motion. A prototype system compatible with atomic force microscopy is established. And the system’s performance is validated using a repetitive control with the recently developed optimized passband loss filter, demonstrating nanometric precision in large-range and high-frequency scanning. The experimental results reveal that the proposed system achieves a precision of 17.6 nm (RMSE) for a 2 mm triangular wave at 1 Hz and 8.2 nm (RMSE) for a 20 μm triangular wave at 80 Hz. Further validation through atomic force microscopy confirms the system's capability in large-range and high-speed characterization. These results suggest that the proposed system could significantly advance the use of large-stroke reluctance-actuated positioners for millimeter-range nano-precision applications.

Keywords: Control Application in Mechatronics, Design Optimization in Mechatronics, Medical Robotics/Mechatronics
Abstract: This paper presents the design, implementation, feedback stabilization, and experimental validation of a novel permanent magnet levitation system. Conventionally, magnetic levitation systems utilize electromagnets to levitate magnetic objects against gravity by stabilizing them around equilibrium points at which the applied magnetic force balances the gravity. This magnetic force must be dynamically adjusted by means of a stabilizing feedback loop, which is established by easy control of the electromagnet voltage. Despite the key advantage of easier control, electromagnets often produce much weaker magnetic forces compared to permanent magnets of similar size, weight, and cost. Therefore, this paper proposes the use of a permanent magnet to produce the magnetic force necessary for levitation, and the use of a linear servomotor to control the magnitude of this force by adjusting the distance between the magnet and the levitating object. To demonstrate this idea in practice, an experimental setup is designed, prototyped, and successfully stabilized using a computer-based feedback control loop.

Keywords: Design/control of MEMS-nano devices, Control Application in Mechatronics, Applications of nano technology
Abstract: This paper proposes the direct phase correction phase locked loop (DPCPLL) for simple and robust synchronization of two resonant MEMS mirrors for a Lissajous scan. The DPCPLL, used in a master-slave synchronization structure, runs the slave mirror at the reference frequency and uses the phase of the driving signal to compensate for the synchronization error directly. The DPCPLL merges synchronization control and a PLL, allowing a simple SISO control. The performance of the proposed DPCPLL is assessed based on the vibration immunity of the synchronization. A PID-based DPCPLL and an LQG-based DPCPLL achieve RMS synchronization errors of 87 ns and 69 ns, respectively, which are improvements compared to 118 ns achieved by the conventional structure with a synchronization controller on top of a PLL-operated mirror. The increase of the stability of the Lissajous pattern under a vibration has benefits in applications such as scanning time of flight lidars or Doppler wind lidars.

Keywords: Control Application in Mechatronics, Human -Machine Interfaces
Abstract: A robot-assisted force control system for stable ultrasound imaging has been developed for abdomen intervention. The system aims to integrate 6-DoF robot arm, 6-axis force/torque sensor, and US probe, featuring real-time compensation for respiratory disturbance. Following the procedural workflow, the system has two operational modes. The first, rooted in admittance control, swiftly positions the robotic-held ultrasound for efficient registration. The second mode, employing the proposed adaptive control, ensures stable contact despite respiratory motion influences, enhancing procedural resilience and effectiveness. The adaptive controller predicts and eliminates disturbances more effectively than the baseline admittance controller, thanks to its utilization of the pseudo-periodic nature of respiration. The efficacy of the adaptive controller has been verified through experiment with a sponge abdomen phantom, demonstrating significant improvements on force regulation.

Keywords: Learning and Neural Control in Mechatronics, Control Application in Mechatronics
Abstract: The traditional methodology utilized in dynamic tracking control synthesis is usually model-based, and therefore, the performance is highly dependent on a precise mathematical model. However, with the growth in system complexity, extremely precise dynamic models for modern robotic and automation systems are very hard to obtain. This challenge has sparked the interest of researchers in moving toward data-driven learning-based concepts, specifically aiming to fully exploit the abundant data available to learn better controls. Along this research direction, continued efforts have been spent on learning a single feedback controller. However, just attempting learning procedures on the feedback controller alone could suffer from severe performance limitations due to its reactive nature, i.e., an error must occur first before any corrective action is taken. In line with this consideration, we propose an integrated two-degree-of-freedom (2-DOF) learning-based tracking control synthesis for high-precision systems, consisting of both feedforward and feedback controllers. Unlike the traditional control design where full knowledge of the dynamics is assumed, we explore the use of actual motion data to iteratively determine the optimal controller parameters using gradient-based optimization. The key step here is to estimate the gradient and Hessian of the cost function without a priori knowledge about the dynamics. Experiments are further conducted based on a prototype flexure-based nanopositioner for spiral scanning applications, demonstrating high-precision nanometer-scale tracking performance that is close to the sensor resolution.

Keywords: Control Application in Mechatronics, Robot Dynamics and Control, Design Optimization in Mechatronics
Abstract: This paper introduces a novel high strength Active Ball Joint Mechanism (ABENICS) based on the Inertial Measurement Unit (IMU) for orientation feedback and control. The advanced ABENICS incorporates a sophisticated interplay of specially designed Cross-spherical and Monopole gears, fabricated from Alumigo Hard alloy. Notably, the gear-based joint proficiently drives three rotational degrees of freedom (RDoF) without slippage. The information from the IMU sensor is leveraged to comprehend the orientation of the spherical gear, enabling accurate positioning to its predefined setpoint using the developed control method. During system startup, the IMU feedback also aids in homing the spherical gear, ensuring a seamless transition to normal operation. The experimental findings affirm the efficacy of the developed control method, showcasing a significant reduction in positioning errors. The paper also introduces the development and experimentation of a robotic arm with ABENICS mechanism as the shoulder joint. The paper concludes by discussing various applications of ABENICS mechanism in robotics.

Keywords: Underwater robotics, Legged Robots, Control Application in Mechatronics
Abstract: The thruster-assisted underwater hexapod robot can walk on the underwater structure with any dip angle. However, the structure is generally deformable due to complex coverings, complicating the leg-terrain interaction dynamics and increasing the difficulty of steering the robot. Here, we propose and experimentally implement an energy-based control method for a thruster-assisted underwater hexapod robot with C-shaped legs. The key idea is to calculate the robot's energy loss during locomotion and use thruster forces to compensate for it. First, we establish a leg-terrain interaction mechanics by considering the leg's special shape and the terrain's viscoplastic characteristics. Then, we use it to calculate the robot's required energy for tracking the predesigned locomotion. Next, based on the multipart control method for monopod robots only driven by legs, we propose a new energy-based control method to coordinate thruster forces and hip joint torques. The torques aim to make legs track the predesigned gaits, and thruster forces are designed according to the remaining energy determined by subtracting the spent energy from the required energy. Finally, the contrastive lakebed locomotion experiment results show that our controller can steer the robot through deformable terrains more smoothly.

Keywords: Aerial Robots, Sensors and Sensing Systems, Unmanned Aerial Vehicles
Abstract: In the realm of aerial vehicle navigation, the reliance on satellite-based and external localization methods presents vulnerabilities to various interferences. This drives the necessity for a self-sufficient absolute navigational system. Image-based localization methods, particularly Absolute Visual Localization (AVL), directly determine the pose in the global frame from a given image. A workflow using 360-degree panoramic images for image-based localization, driven by a Deep Convolutional Neural Network (DCNN), is proposed. Utilizing panoramic imagery offers the advantage of encompassing visual information from all angles. Synthetic data generated from multiple sources such as photogrammetry, Open Street Map (OSM), and official 3D building data are used to train the localization network. Domain adaptation using cycleGAN is also used to bridge the Sim2Real gap and enhance model performance. Utilizing OSM features are shown to improve localization performance (median Euclidean error) by at least 13%, and a further 20% with cycleGAN dataset augmentation. Closed loop control is also achieved using a trained model, enabling a quadrotor prototype to hover within a 1 m circle.

Keywords: Software Design for System Integration, Rapid Prototyping, Wed-based Control of Robotic and Automation Systems
Abstract: Abstract - Amidst escalating labor costs and the imperative for workplace safety, automation has become a crucial trend. Yet, the substantial expenses and technical complexities of robotic systems, demanding significant time and expertise for design and deployment, limit their adoption in small enterprises. To tackle this, we present the WinGs Operating Studio (WOS) - a novel low-code platform for robotic arm operations. WOS stands out by effortlessly integrating with a wide range of robotic arms and accessories, including various sensors and end effectors, through flowchart programming and versatile APIs. This facilitates straightforward implementation of advanced features like multi-robot cooperation and external system interactions. The paper delves into WOS’s design, capabilities, and architecture, highlighting its role in lowering technical barriers and operational costs. Performance evaluations on ARM-based Single-Board Computers and real-world scenarios, such as automated coffee making with dual robotic arms and VR controlled spray painting, underscore WOS's potential to empower small businesses with robotic automation.

Keywords: Human -Machine Interfaces, Control Application in Mechatronics, Machine Learning
Abstract: As the aging and disabled populations grow, the demand for effective assistance for human locomotion in daily activities such as sit-to-stand (STS) has been increasing. Wearable exoskeletons is a promising technology in reducing the effort required for STS. This study explores the sensor fusion of electroencephalography (EEG) signals, which reveal pre-movement intentions, with inertial measurement unit (IMU) data, offering real-time motion information for enhanced knee exoskeleton control in STS assistance. The EEG-IMU sensor fusion approach is designed to improve the temporal accuracy and robustness of STS intention detection. By detecting STS intentions with lower latencies, the knee exoskeleton can provide timely and smooth support, enhancing the user experience. The proposed method further reduces system latency, enabling rapid interaction between the user and the exoskeleton. Experimental results demonstrate the effectiveness of the proposed brain computer interface (BCI)-enhanced knee exoskeleton for improving STS movement efficiency and user experience.

Keywords: Vehicle Control, Planning and Navigation, Robot Dynamics and Control
Abstract: This paper presents a novel approach to automated drifting with a standard passenger vehicle, which involves a Nonlinear Model Predictive Control to stabilise and maintain the vehicle at high sideslip angle conditions. The proposed controller architecture is split into three components. The first part consists of the offline computed equilibrium maps, which provide the equilibrium points for each vehicle state given the desired sideslip angle and radius of the path. The second is the predictive controller minimising the errors between the equilibrium and actual vehicle states. The third is a path-following controller, which reduces the path error, altering the equilibrium curvature path. In a high-fidelity simulation environment, we validate the controller architecture capacity to stabilise the vehicle in automated drifting along a desired path, with a maximal lateral path deviation of 1 m. In the experiments with a standard passenger vehicle, we demonstrate that the proposed approach is capable of bringing and maintaining the vehicle at the desired 30 deg sideslip angle in both high and low friction conditions.

Keywords: Modeling and Design of Mechatonic Systems, Design Optimization in Mechatronics
Abstract: This paper analyses and evaluates the cross-scan error of a large-size polygon mirror-based laser scanning system for industrial stereolithography (SLA). The polygon mirror (PM) is often used for fast scanning applications due to its superior scanning speed and large scanning angle. However, PM-based laser scanning systems are prone to cross-scan errors, restricting scanning precision. The facet tilt and scanhead dynamics are considered as two primary sources contributing to cross-scan errors. The datum-to-shaft error by manufacturing imperfections is modeled as the main cause of the facet tilts in the investigated PM-based scanner. This datum-to-shaft error varies due to radius expansion by the PM at high-speed rotations, leading to a 10 micrometers variation in the cross-scan error. The scanhead dynamics are measured by a vibrometer and characterized by non-deterministic vibrations and the deterministic periodic excitation. The total scanning precision of the large-size PM-based laser scanning system is approximately 160 micrometers mainly due to the datum-to-shaft error, limiting the precision of the PM based industrial SLA printer without any compensation.

Keywords: Planning and Navigation
Abstract: Planning a global reference path under final pose constraints is necessary for unmanned mining trucks to ensure the seamless execution of the loading process. However, irregular mountain shapes in large-scale mining areas lead to a substantial increase in the complexity of determining appropriate node expansion parameters of path planning. Furthermore, conventional methods which utilize fixed parameters in node expansion exhibit a dramatic rise in path length and computation time due to diverse obstacle distribution in open-pit mines. To address this challenge, we propose a novel Two-Stage Dichotomy Hybrid A* (TSD-HA*) to determine near-optimal parameters in the node expansion process. Firstly, we generate convex polygonal obstacles through clustering on the grid map, thus reducing unnecessary node searches caused by U-shape obstacles. Subsequently, a two-stage dichotomy process is proposed to optimize steering angle and step length respectively, which yields near-optimal successor nodes and accelerates the node expansion process. To evaluate the effectiveness and computational efficiency of the proposed method, we conduct field experiments at an open-pit mine. The results demonstrate that our proposed method outperforms other conventional methods in terms of path length and computation time.

Keywords: Biomechatronics, Control Application in Mechatronics, Modeling and Design of Mechatonic Systems
Abstract: Within cataract surgery, posterior capsule (PC) polishing is a specific procedure that has demonstrated value toward improving surgical outcomes, yet is not commonly performed by surgeons due to the risk of doing so. In this work, a robotic system is used to perform the polishing procedure through three main contributions: external stabilization of the eye using a dedicated docking device, regulating intraocular pressure through feedback control, and improving the robot-tracking performance to result in an accurate polishing procedure. To validate the methodology, polishing was performed on four ex vivo pig eyes by mimicking the residual lens on the PC with an evenly distributed layer of glue. Fast and accurate polishing results were achieved and complete glue removal was accomplished in all experiments without any PC rupture or other surgical complications.

Keywords: Biomechatronics, Novel Industry Applications of Mechatroinics
Abstract: In this study, we attempt to accelerate fermentation using a device that mimics the peristaltic movement of the intestine. This is based on the fact that the intestine promotes efficient digestion through peristalsis and fermentation in the intestine. In the intestine, good bacteria are conducting fermentation. Good bacteria have a role in regulating the intestinal environment through fermentation. And, there is a possibility that the acceleration of fermentation is effectively related to the movement of the intestines, such as peristalsis. Therefore, we aim to clarify the relationship between fermentation and peristalsis and further accelerate fermentation using a device that mimics peristalsis. In this paper, as an initial study, experiments were conducted to check the progress of fermentation of materials of different hardness using the device. The results showed that the crushing capacity of the device was low, but its ability to spread liquids was high. This results suggest that fermentation can be controlled by changing the physical characteristics of the fermentation substance and using a peristaltic pump to accelerate fermentation in combination.

Keywords: Biomechatronics, Robot Dynamics and Control, Control Application in Mechatronics
Abstract: Object manipulation has been extensively studied in the context of fixed base and mobile manipulators. However, the overactuated locomotion modality employed by snake robots allows for a unique blend of object manipulation through locomotion, referred to as loco-manipulation. The following work presents an optimization approach to solving the loco-manipulation problem based on non-impulsive implicit contact path planning for our snake robot COBRA. We present the mathematical framework and show high fidelity simulation results for fixed-shape lateral rolling trajectories that demonstrate the object manipulation.

Keywords: Biomechatronics, Human -Machine Interfaces, Modeling and Design of Mechatonic Systems
Abstract: Pressure injuries in immobilized patients pose a global healthcare problem, imposing substantial economic burdens and affecting health and quality of life of those patients. While specialized pressure-redistributing mattresses and contoured foam cushions have been investigated, challenges persist. In this paper, we present mechatronic designs of (i) thigh-buttock (TB) analogue and (ii) instrumented soft pad to study the contact interactions and mechanisms of pressure injury formation in a simulated human body environment. Developed full-scale TB analogue is equipped with embedded vasculature, pressure sensors, and flow sensors, designed to emulate vein collapse dynamics under normal loads. The soft pad is an actively controlled, dynamic, soft support surface discretized into multiple individual actuators with integrated pressure, temperature, and humidity sensors. The integrated sensors allow for continuous monitoring of the contact interactions and environmental conditions at the analogue-pad interface. Effects of developed normalizing pressure distribution algorithm on vein flow at various locations under bony and soft tissues, as well as monitoring of temperature and humidity that are known pressure injury formation factors are demonstrated through extensive experiments. The presented mechatronic design enables controlled physiological simulations contributing towards better understanding of pressure injury mechanisms and potentially leading towards improved pressure injury prevention.

Keywords: Biomechatronics, Modeling and Design of Mechatonic Systems
Abstract: Deriving from the posture of instrument holding of human surgeons, this paper develops a hybrid parallel-serial robot for ophthalmic surgeries. Each serial branch makes use of a compact five-bar mechanism for distal actuation with increased rigidity in the direction of gravity. The designed robot manipulator has a variable remote center of motion (RCM), such that small eye ball motion can be compensated for without translating the entire platform. As such, the alignment can be less time-consuming, as opposed to those fixed RCM designs. To streamline the multi-tool surgery, a passive tool exchange mechanism is proposed. The mechanism utilizes the bi-stable positions of push-push button to load and unload the surgical instrument, whereas the permanent magnets and kinematic coupling on the manipulator serves to constrain the tool with adequate fixation force. The physical prototype confirms the sufficient range of motion for retinal operations and the tool exchange capability.

Keywords: Rehabilitation Robots, Biomechatronics
Abstract: Knee exoskeletons have been utilized for gait rehabilitation in patients after total knee arthroplasty. During the early and middle stance phases of walking gaits, the knee joint activity of these patients is either absent or reduced, which is not conducive to the rehabilitation of normal gaits. Currently, most exoskeletons used for the rehabilitation of patients after TKA correct gait by pre-setting the movement trajectory of the knee joint. However, this method faces challenges in terms of human-machine interaction and safety. This paper proposes a strategy that combines admittance control during the early and middle stance phases with position control during the late stance and swing phases to improve compliance and safety between the wearer and the knee exoskeleton. The exoskeleton can provide support to the knee joint during the early and middle stance phases according to the wearer’s actual movement requirements. The performance and safety of the admittance control were verified through test bench and squat-to-stand experiments, while the gait intervention strategy was validated through a downhill walking experiment.

Keywords: Unmanned Aerial Vehicles, Aerial Robots, Motion Vibration and Noise Control
Abstract: Recent advancements in unmanned aerial vehicle (UAV) and multirotor technology have increased industrial applications, but safety and noise remain challenges. The aim is to devise a method to suppress thrust force vibration in crosswind conditions that apply to small-sized multirotors. A higher harmonic rotational speed control method is proposed based on the position-dependent aerodynamic force model. Second-order harmonic thrust vibration under crosswind conditions is simply modeled, and higher harmonic input is designed only for use in the rotational speed and utilized high torque response performance of the electric motor. The effectiveness of the proposed method is validated through the wind tunnel experiment.

Keywords: Unmanned Aerial Vehicles, Image Processing, Planning and Navigation
Abstract: The water-dropping method is crucial for the aerial firefighting using either fixed-wing or rotary-wing aircraft. When a wildfire occurs, aerial firefighters need to cross the wildfire and extinguish it by dropping water/retardant based on their experiences. It is extremely dangerous for aerial firefighters to carry out such a mission with also the lack of water-dropping accuracy while mainly based on pilot’s experience. In order to improve the precision of water-dropping and reduce the risk to firefighters in aerial firefighting missions, an autonomous water-dropping method with high precision has been proposed for fire spot suppression using unmanned rotary-wing aerial firefighting vehicles. Once a fire spot location is determined, the unmanned aerial firefighting vehicle will fly to and hover above the fire spot based on GPS navigation information autonomously. Then a feedback controller drives the unmanned aerial firefighting vehicle to approach the fire spot quickly based on the relative distance difference perceived by an infrared thermal camera. Meanwhile, a wireless trigger is utilized to execute the drop action when the precision or time conditions for water-dropping are met. Finally, the unmanned aerial firefighting vehicle returns to the ground station safely. The designed method implemented and tested in the outdoor field with a DJI M300 quadrotor unmanned aerial vehicle equipped with an onboard H20T payload. The experiment results have demonstrated the effectiveness of the designed method.

Keywords: Unmanned Aerial Vehicles, Robot Dynamics and Control, Aerial Robots
Abstract: The cable-suspended transportation using multiple UAVs has gradually gained attention in UAV logistics fields over the past decade, owing to their greater efficiency compared to a single UAV transportation with heavy manipulators. This study further developed a centralized cable-linked dual-multirotor system prototype, which is expected to handle cargo of arbitrary shape and weight, attached with two hooks for loading, transporting, and unloading. To realize this, we proposed a novel Tug-of-War (ToW) method for loading/unloading and a modeling approach for transportation that treats the cargo as a disturbance. The control algorithm of the system adopted a hybrid control strategy formed by combining the model reference adaptive nonlinear model predictive control (MRA-NMPC) and the geometric control. The numerical simulation results successfully demonstrated the performance of the dual-multirotor system, and the feasibility of the ToW method was verified.

Keywords: Unmanned Aerial Vehicles, Wed-based Control of Robotic and Automation Systems
Abstract: This paper dives into the design of the complete autonomous system for replacing lithium-polymer batteries of small-scale UAVs improving extended flight times and preventing battery damages for aerial safety. The Robotic Ground System’s (RGS) development consisting of three sub-systems, focuses on a quick-charge power station to provide extensive flight time and eliminate long charging disturbances during ongoing missions. Accompanied by solar panels, its power comes from the sun’s renewable energy, providing power to the entire system.

Keywords: Control Application in Mechatronics, Network Robotics, Unmanned Aerial Vehicles
Abstract: In a scenario where two unmanned aerial vehicles (UAVs) are equipped with directional antennas for point-to-point communication, maintaining high-performance communication requires continuous adjustment of antenna orientations. This paper presents a novel received signal strength indicator-based nonlinear static state feedback control law to achieve this under the unknown motions of the UAVs and the absence of global positioning system data. Our proposed method ensures convergence to the best orientation for almost all initial states of the closed-loop system when the UAVs are stationary. Furthermore, the closed-loop system achieves tracking of the best orientation with an error during motion. We experimentally demonstrate the effectiveness of the proposed method in solving the directional antenna pair alignment problem.

Keywords: Unmanned Aerial Vehicles
Abstract: Tailsitter unmanned aerial systems (UAS) are vehicles that, through rigid body rotation, are capable of operating in and switching between the vertical take-off and landing (VTOL) and fixed-wing flight regimes. The typical approach for control design for tailsitter UAS considers the aerodynamics of the wings as a disturbance to be avoided or suppressed, specifically during the pure VTOL and transition flight regimes. This can result in overly conservative controllers or otherwise degraded tracking performance. To address this, here we present a unified design and analysis approach for a controller that explicitly accounts for the effect of wing aerodynamics for tailsitter UAS operating in pure-VTOL, pure-forward flight and transition flight regimes. The overall control architecture uses feedback linearization with nested control loops, with position controlled in the outer-loop and attitude controlled in the inner loop. The outer loop uses feedforward knowledge of the aerodynamic forces from the mission planning stage, while the inner loop is designed assuming that moments generated by the aerodynamic forces are negligible. We derive analytical conditions that guarantee stability of the outer loop and inner loop controllers in the presence of bounded uncertainty in the aerodynamic forces and moments. Further, we provide performance bounds for both the outer and inner loop controllers in the presence of these unmodeled or uncertain aerodynamic forces and moments. Finally, we use a high fidelity flight dynamics simulation of a quadrotor biplane tailsitter to perform a statistical analysis of the control architecture performance to illustrate the stability result and quantify controller performance.

Keywords: Compuational Models and Methods, Actuators in Mechatronic Systems, Modeling and Design of Mechatonic Systems
Abstract: This paper explores the influence of thermopiezoelectricity in piezoelectric actuators, specifically focusing on multilayer stack actuators. The research aims to investigate the impact of the pyroelectric and electrocaloric effects on the positioning, electric potential, and temperature of these actuators. To accomplish this, a custom finite element code that considers the three fully coupled field equations of thermopiezoelectricity is implemented in MATLAB. In addition, the study is extended to explore the influence that the temperature-dependent piezoelectric strain coefficients have on the stack actuator's behaviour.

Keywords: Virtual Reality and Human Interface, Actuators in Mechatronic Systems, Tele-operation
Abstract: Magnetorheological (MR) fluids are innovative materials consisting of a suspension of non-colloidal and magnetically polarizable particles in a non-magnetic medium. Their rheological properties change rapidly, stably, and repeatedly when applying magnetic fields. Therefore, MR fluids are used in several engineering applications, such as dampers, brakes, and clutches. Consequently, we focus on the design of a miniature-sized MR Device for a lightweight haptic device. To achieve the above goal, we measured and modeled the rheological properties of a sample of SoftMRF. Subsequently, the torque performances of three types of rotor structures were estimated and compared using this model and the results of electromagnetic analyses. In addition, we designed the miniature MR fluid device with lightweight (< 60 g) and high torque (> 0.2 Nm).

Keywords: Actuators, Compuational Models and Methods, Modeling and Design of Mechatonic Systems
Abstract: Piezoelectric stick-slip stepping actuators have emerged as a promising candidate, offering merits of high speed, compact design, and controllability. Despite advancements in this category, there is a necessity for a comprehensive analysis method to systematically investigate and predict the complex interactions of key input parameters such as friction at contact, inertia, driving signal, and mechanical design simultaneously. Hence, this work presents dynamic analysis using a finite element approach to reveal the complete phenomenon of the stick-slip motion. The parallel configuration of the linear piezoelectric stick-slip actuator is selected to demonstrate the effect of control parameters on its stepping displacement. An actuator prototype is fabricated, and experiments are conducted to test the efficacy of the numerical analysis. This numerical method is envisioned to serve as a tool to bridge the design and operational aspects of the stick-slip actuator. Therefore, this work establishes the foundation for subsequent design and optimization studies, aiming to advance the development of high-performance piezoelectric actuators.

Keywords: Actuators, Control Application in Mechatronics
Abstract: The response of robot actuators to various dynamic interactions during contact tasks is not trivial because there exists a tradeoff between actuator-thrust force density and back-drivability. Although hybrid actuation approaches are promising, complex transmission mechanisms are necessary to synthesize forces from heterogeneous actuators. This study presents a novel concept of a fusion hybrid linear actuator to address the fundamental problems in conventional hybrid actuation approaches. The concept embodies an integrated structure of an air cylinder and a linear motor and shares the moving spaces of the piston and moving part of the linear motor inside the compact housing of the actuator. Herein, the design strategy requirements and its structural optimization processes are discussed. A kinetic friction model of a pneumatic cylinder that considers a piston structure is proposed to improve the force characteristics during dynamic interaction. Furthermore, a quantitative benchmark test is developed to maintain the contact force constant against a load actuator, to evaluate the disturbance resistance under a wide range of target contact force conditions. The concept and performance were validated by experiments comparing the proposed hybrid actuation condition with conventional pneumatic actuation conditions.

Keywords: Actuators, Flexible Manipulators and Structures, Modeling and Design of Mechatonic Systems
Abstract: This paper presents a novel approach to improving the self-repair capabilities of soft robots by introducing a self-contained robotic blood vessel mechanism. Aimed at addressing the physical weakness of soft robots from sharp objects, the proposed system is inspired by biological healing processes, utilizing water-absorbent materials to seal damage actively. The study validates the effectiveness of this mechanism through experimental evaluation, showing that the self-healing function is enhanced as the channel area within the wound cross-section is increased. Future directions for research include the optimization of material placement and the adaptation of the system for repeated injuries, paving the way for more resilient inflatable soft robots with active self-healing functions.

Keywords: Actuators, Human -Machine Interfaces, Biomechatronics
Abstract: Sustainable power supply is a challenge for portable and wearable electronic devices such as cell phones and headsets. To address this, researchers proposed capturing biomechanical energy from human motion to generate electricity. This paper proposed and developed a lightweight wearable device to capture the biomechanical energy from the human knee motion. To reduce the effect of inertial force on human gait, we developed a lightweight and compact transmission chain to convert the bidirectional rotation of the knee to a unidirectional rotation of the generator. Two input bevel gears with opposite one-way bearings on the same shaft are engaged with a single output bevel gear of the generator thereby only one input bevel gear is engaged for each input direction, achieving unidirectional output. In addition, to reduce velocity fluctuation and further minimize the effect of inertial force, a flywheel was fixed to the motor shaft via a gearbox. A prototype of the wearable device was developed and tested on a subject walking on a treadmill. Experimental results shows the flywheel enabled the harvester to achieve a continuous output while halving voltage fluctuations compared to a conventional harvester. The harvesters average power output can reach 0.11 W with minimal effects on the subject's walking gait.

Keywords: Medical Robotics/Mechatronics, Image Processing, Machine Learning
Abstract: This paper proposes a modified method for training tool segmentation networks for endoscopic images by parsing training images into two disjoint sets: one for rectangular representations of endoscopic images and one for polar. Previous work demonstrated that certain endoscopic images may be better segmented by a U-Net network trained on the original rectangular representation of images alone, and others performed better with polar representations. This work extends that observation to the training images and seeks to intelligently decompose the aggregate training data into disjoint image sets - one ideal for training a network to segment original, rectangular endoscopic images and the other for training a polar segmentation network. The training set decomposition consists of three stages: (1) initial data split and models, (2) image reallocation and transition mechanisms with retraining, and (3) evaluation. In (2), two separate frameworks for parsing polar vs. rectangular training images were investigated, with three switching metrics utilized in both. Experiments comparatively evaluated the segmentation performance (via Sorenson Dice coefficient) of the in-group and out-of-group images between the set-decomposed models. Results are encouraging, showing improved aggregate in-group Dice scores as well as image sets trending towards convergence.

Keywords: Machine Learning, Part Feeding and Object Handling , Sensor Integration, Data Fusion
Abstract: This paper presents a novel manipulation strategy that uses keypoint correspondences extracted from visuo-tactile sensor images to facilitate precise object manipulation. Our approach uses the visuo-tactile feedback to guide the robot's actions for accurate object grasping and placement, eliminating the need for post-grasp adjustments and extensive training. This method provides an improvement in deployment efficiency, addressing the challenges of manipulation tasks in environments where object locations are not predefined.

We validate the effectiveness of our strategy through experiments demonstrating the extraction of keypoint correspondences and their application to real-world tasks such as block alignment and gear insertion, which require millimeter-level precision. The results show an average error margin significantly lower than that of traditional vision-based methods, which is sufficient to achieve the target tasks.

Keywords: Medical Robotics/Mechatronics, Image Processing, Machine Learning
Abstract: In this study, we propose a method to identify and avoid multiple reflections and posterior echo enhancement by robotic echocardiography, with the aim of improving the search accuracy of the basic examination cross-section acquisition system developed by the authors. We developed a discrimination algorithm based on the characteristics that a layered false image appears at integer multiples of the distance from the probe to the real image for multiple reflections, and a bar-shaped false image appears behind the pericardium for posterior echo enhancement. We then constructed a method to avoid multiple reflections and posterior echo enhancement by using the proposed identification method. When the left ventricular wall of the closed loop was not detected because of multiple reflections, the posture of the probe was adjusted, and the search was performed again. When the center of gravity of the detected ventricular septum was included inside the contour of the posterior echo enhancement, the detected ventricular septum was judged as a false positive. The evaluation of the identification method was performed on 300 images, of which 100 images each showed multiple reflections and posterior echo enhancement and 100 images showed no artifacts. The results showed that multiple reflections and posterior echo enhancement were detected with an F-score of 82.1 % and 90.7 %, respectively, suggesting the validity of the identification method. The results showed that the robot was able to detect the left ventricular wall and ventricular septum in a closed loop with 21.3 % and 62.7 % accuracy, respectively, suggesting the effectiveness of the avoidance method.

Keywords: Machine Learning, Intelligent Process Automation, Fixture and Grasping
Abstract: Autonomous manipulation in robot arms is a complex and evolving field of study in robotics. This paper proposes work stands at the intersection of two innovative approaches in the field of robotics and machine learning. Inspired by the Action Chunking with Transformer (ACT) model, which employs joint angle and image data to predict future movements, our work integrates principles of Bilateral Control-Based Imitation Learning to enhance robotic control. Our objective is to synergize these techniques, thereby creating a more robust and efficient control mechanism. In our approach, the data collected from the environment are images from the gripper and overhead cameras, along with the joint angles, angular velocities, and torques of the follower robot using bilateral control. The model is designed to predict the subsequent steps for the joint angles, angular velocities, and torques of the leader robot. This predictive capability is crucial for implementing effective bilateral control in the follower robot, allowing for more nuanced and responsive maneuvering.

Keywords: Learning and Neural Control in Mechatronics, Actuators in Mechatronic Systems, Machine Learning
Abstract: The manufacturing industry is experiencing an increasing demand for improved production efficiency. Achieving precise control of high-performance, high-speed core-type permanent magnet linear motors is therefore essential to meet this need. The primary objective of this research is to address the challenges posed by complex disturbances, such as cogging force, which are influenced by both position and velocity and significantly degrade tracking performance. To overcome these problems, this research employs a two-step approach. Firstly, the Kalman smoother is used to accurately estimate the state variables and disturbances. Secondly, Gaussian Process Regression (GPR) is applied to establish a relationship between these state variables and disturbances, allowing the generation of disturbance compensation signals in arbitrary trajectories. A method introduced in this research streamlines the GPR computations, allowing efficient handling of large estimated data sets. The results of this study demonstrate a significant improvement in tracking performance compared to alternative data interpolation techniques such as smoothing splines. To validate this improvement, tracking control experiments were performed using a stage-type experimental machine equipped with core-type linear motors.

Keywords: Fuel Cells and Alternative Power Sources, Service Robots, Machine Learning
Abstract: Predictive energy management models considerably advance financial and environmental analyses of industrial robotic manipulator energy consumption. As industries increasingly prioritize sustainability and cost-effectiveness, optimizing energy utilization becomes crucial. Consequently, this paper presents VoltaResBot, a machine learning-driven predictive technoeconomic model for optimal energy management in multi-component robotic systems integrated with photovoltaics, electricity grid, and storage. VoltaResBot utilizes Support Vector Machines (SVM) to predict and optimize energy consumption, facilitating precise control of a 6 Degrees of Freedom (6 DoF) robotic manipulator. The findings of VoltaResBot indicate its effectiveness in achieving optimal energy utilization, significantly reducing environmental impact, and potentially contributing to financial savings. Key Performance Indicators (KPIs) employed in the evaluation include Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and R-squared (R2), presenting the model's accuracy and reliability. Comparative analyses with traditional machine learning models further demonstrate the superior performance of VoltaResBot, establishing it as a robust and promising tool for enhancing both the financial and environmental dimensions of industrial energy management.

Keywords: Modeling and Design of Mechatonic Systems, Actuators in Mechatronic Systems, Actuators
Abstract: This paper focuses on the application of soft robotics in the area of social interaction, and presents a modular approach on the design of a soft robotic neck for integration with the social robot HARU. The proposed design incorporates soft robotics and additive manufacturing principles, enhancing safety through compliance for absorbing contacts with users or objects, while modularity allows for easy replacement or upgrade to meet HARU's specific application requirements. The paper discusses the conceptual design specifics of the soft robotic neck and provides an overview of the prototype development stages and its main functionalities.

Keywords: Modeling and Design of Mechatonic Systems, Actuators, Control Application in Mechatronics
Abstract: This paper investigates the use of imposed rotations of an underwater cylinder reversing direction at a desired frequency in order to transmit vortices in a flow and enable a new method of underwater force transmission. A hydrofoil interacts with controlled vortices, which modulates the forces on the hydrofoil. The motivation is to assist and resist users walking on an underwater treadmill in a continuous-flow aquatic therapy pool used for gait rehabilitation, utilizing buoyancy to reduce apparent limb weight and impact force while walking. Previously, we have shown this concept on a small scale with a passive double pendulum when the incoming fluid flow is highly uniform. This paper shows that force transmission is also possible in such a harsh environment (a continuous-flow aquatic therapy pool) where the incoming flow is highly non-uniform and at a much larger scale. By measuring forces acting on a downstream hydrofoil, we show that the frequency of the vortices generated upstream can be perceived by the downstream hydrofoil.

Keywords: Modeling and Design of Mechatonic Systems, Control Application in Mechatronics, Design Optimization in Mechatronics
Abstract: The control of underactuated systems is a challenging problem specifically when the mechatronic systems’ control design and implementation are involved. This paper presents a design for a reaction wheel inverted pendulum setup in which variable configurations of the pendulum are achieved by adjusting the position of the overall center of mass of the pendulum. The paper discusses the mechatronics system design and presents methods to identify the dynamic system parameters experimentally. The control system is then analyzed for stability condition at various configurations of center of mass, and a stabilizing control is demonstrated by experimentally implementing of a modern LQR- based state feedback controller.

Keywords: Modeling and Design of Mechatonic Systems, Biomechatronics, Rehabilitation Robots
Abstract: Post-stroke patients and individuals undergoing hand rehabilitation often grapple with prolonged and discomforting recovery processes. Hand exoskeleton products currently available in the market do not leverage precise input of therapist-assisted movements. Recognizing these challenges, technological solutions have emerged to assist and expedite rehabilitation, demanding practicality in lightweight design and user-centric features. Controlled with a sensorized soft glove (SSG), the designed hand exoskeleton focuses on user-centric attributes, including lightweight construction, durability, and comfort. The constructed hand exoskeleton leverages printable finger segment mechanisms and other lightweight components, enhancing replicability. The mechatronic system, featuring flex sensors and micro linear actuators, adopts a modular design, streamlining setup, storage, troubleshooting, and component replacement. A central microcontroller-driven main board ensures immediate communication between flex sensors on the soft glove and actuators on the hand exoskeleton, facilitating replication of individual finger flexion and extension movements. Experiments were performed to assess the hand exoskeleton's performance across various hand configurations using flex sensors placed where individual finger metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints are located on the printed segments, with RMSE between input rotational movements from the SSG and output rotational movements from the hand exoskeleton is less than 9.03 deg. Integrating printed finger segments promotes adaptability to diverse hand shapes and guarantees each user a personalized and comfortable fit. The flex sensor-based results show that the intended flexion or extension of the MCP or PIP joint on the SSG can be replicated by the hand exoskeleton.

Keywords: Modeling and Design of Mechatonic Systems, Neural Networks, Mobile Robots
Abstract: Detecting falls among the elderly and alerting their community responders can save countless lives. We design and develop a low-cost mobile robot that periodically searches the house for the person being monitored and sends an email to a set of designated responders if a fall is detected. In this project, we make three novel design decisions and contributions. First, our custom-designed low-cost robot has advanced features like omnidirectional wheels, the ability to run deep learning models, and autonomous wireless charging. Second, we improve the accuracy of fall detection for the YOLOv8-Pose-nano object detection network by 6% and YOLOv8-Pose-large by 12%. We do so by transforming the images captured from the robot viewpoint (camera height 0.15m from the ground) to a typical human viewpoint (1.5m above the ground) using a principally computed Homography matrix. This improves network accuracy because the training dataset MS-COCO on which YOLOv8-Pose is trained is captured from a human-height viewpoint. Lastly, we improve the robot controller by learning a model that predicts the robot velocity from the input signal to the motor controller.

Keywords: Space Robotics, Compuational Models and Methods, Modeling and Design of Mechatonic Systems
Abstract: SSRMS-type Manipulator is a typical type of space manipulator featuring 7-degree-of-freedom offset configuration with redundancy characteristic. It is challenging to solve inverse kinematics in high efficiency, make the upmost of redundancy characteristic, and select optimal redundant parameter. This paper proposes an analytical inverse kinematic method, named three-continuous-parallel-Link Direction Vector Parameterization (LDVP), in the theory of Conformal Geometric Algebra. This method employs the direction vector of the axis of parallel Joint 3, Joint 4, and Joint 5 as the parameter, and selects the optimal parameter according to context plan-points in a given trajectory. The process of solving inverse kinematics is divided into two steps, including solving joint positions and joint variables. The average solution time of forward and inverse kinematics is 9.79 us and 0.25 ms respectively. The continuous path tracking experiment verifies that all seven joints changing to pursue the optimal configuration, which makes full use of redundancy characteristic.

Keywords: Design/control of MEMS-nano devices, Control Application in Mechatronics, Micro-Electro-Mechanical Systems
Abstract: Synchronized operation of multiple micro-electromechanical systems (MEMS) scanning axes is crucial for applications such as Lissajous scanning. This paper presents a precise linear model and a synchronization control with a fixed frequency ratio for two electrostatically actuated MEMS mirrors driven in parametric resonance. The precise linearized model of the nonlinear resonant mirror is extended for the two-axis synchronization. Based on a master-slave architecture, each mirror is controlled by an individual independent phase-locked loop (PLL) with the displacement current self-sensing, while the duty cycles of the square wave driving signals are either used for amplitude control or phase synchronization to keep a fixed frequency ratio between both mirrors. The dynamics of the controlled nonlinear MEMS mirror at the nominal operation point are analyzed based on a period-to-period energy conservation method, leading to a simple linear model for control design. The derived model and the synchronized operation of the proposed system are verified by measurements, demonstrating an RMS center pixel synchronization error of 0.09 mrad for the master and 0.13 mrad for the slave and providing good maintenance of the high-resolution scanning pattern under environmental influences.

Keywords: Control Application in Mechatronics, Design Optimization in Mechatronics, Medical Robotics/Mechatronics
Abstract: This paper presents experimental results to verify a novel concept of magnetic manipulation in which arrays of permanent magnets and electromechanical actuators generate and effectively control magnetic fields, through which, magnetic objects can be manipulated from a distance without any direct contact. This concept is realized by an experimental setup that consists of six diametrically magnetized permanent magnets actuated by rotary servomotors to control their directions, by which, the aggregate magnetic field is controlled in a planar circular workspace. To leverage this magnetic field for control of magnetic objects inside the workspace, a feedback loop must be established to command the servomotors based on the positions of these objects measured in real time. A suitable control law is developed for this feedback loop, and is verified by experiments, which demonstrate successful results. The experimental results are compared with those generated by computer simulations under similar conditions.

Keywords: Control Application in Mechatronics, Motion Vibration and Noise Control
Abstract: This paper presents a compliance-based controller tailored to address potential environmental interactions encountered by a plant during its motion. The controller's application involves empowering an operator to delineate a trajectory through the exertion of an input force. This trajectory must be followed while permitting a prescribed degree of compliance, thereby facilitating soft contact with the environment. This capability enhances the system's ability to smoothly interact with non-fixed obstacles. However, scenarios requiring sustained contact necessitate the implementation of a force-based controller. Consequently, the proposed controller integrates an admittance controller for trajectory generation and a variable position-based compliance controller to regulate interactions with the environment effectively.

Keywords: Control Application in Mechatronics, Actuators, Actuators in Mechatronic Systems
Abstract: Pneumatic drives are commonly used in automation technology, where their motion must follow certain reference trajectories. To maximize productivity, these trajectories should be as fast as possible and at the same time still feasible to track. The limiting factors therein are that the pressure dynamics are not negligibly fast, the air mass flow through the control valves is subject to pressure-dependent constraints, and the dynamics of the mechanical and pneumatic subsystems are coupled to each other. The goal of this work is to generate quasi time-optimal trajectories for pneumatic drives considering all the aforementioned dynamics and constraints in a model-based way. As a foundation, it is first analyzed how the actuator dynamics and nonlinear state-dependent constraints affect the motion of the drive. Then, the quasi time-optimal control problem for trajectory generation is formulated and solved numerically offline. The resulting trajectories are validated through experiments on the drive. The experimental outcomes show that the trajectories are both dynamically feasible and utilize the available control input efficiently.

Keywords: Control Application in Mechatronics, Novel Industry Applications of Mechatroinics, Modeling and Design of Mechatonic Systems
Abstract: Automation has revolutionized scientific research, particularly in cell culture, where it enhances efficiency and minimizes variability. Traditional cell culture faces challenges, often leading to stress-induced cell senescence. To address these challenges, we are developing an enclosed, automated system with a robotic fluid handling system and 60 independent bioreactors. Aiming for clinical applications, the system is required to maintain tight environmental control for optimal cell culture conditions. This paper reports on the development of the control system for maintaining the gaseous carbon dioxide (CO2) concentration within the enclosed system. In particular, we develop a predictor feedback CO2 controller to regulate the CO2 concentration. A baseline traditional feedback controller is also implemented for comparison. This work contributes to advancing automated cell culture systems, emphasizing the importance of precise environmental control for higher-quality cell cultures. The developed predictor feedback CO2 controller offers a promising control solution to reducing stress-induced variations and will be suitable for clinical applications.

Keywords: Control Application in Mechatronics
Abstract: Time delay is a critical aspect concerning stability and robustness of controlled systems. This paper considers a class of linear time-delayed systems where the distribution and the maximum change rate of the delay are known. For these systems, it proposes a method to investigate their stability. Therefore, the delay is partitioned into intervals with occurrence probabilities to approximate the delay distribution. The number of intervals can be freely chosen to trade off between complexity and the quality of the approximation of the distribution. Considering this delay distribution approximation, the system is analysed for exponential stability in mean-square sense (ESMSS), and the benefits of this method are shown in numeric examples. It is revealed that by better approximating the delay distribution the maximum allowable delay can be increased. Further, if the delay change rate bound gets small, the conservatism is reduced even more. The result of this stability analysis is a statement for the expected value of the states at infinite time. Thus, no statement about stability for short time frames is made, which needs to be considered when choosing this approach.

Keywords: Artificial Intelligence in Mechatronics, Fault Detection and diagnosis in Manufacturing, Intelligent Process Automation
Abstract: In this work, machine learning is applied to develop a LSTM-AutoEncoder for anomaly detection in three-axis CNC machines. This anomaly detection network is then transferred to another three-axis CNC machine for chatter detection, using significantly less data. This network is then extended to five-axis CNC machines by using the encoder from the three-axis CNC machine to develop an anomaly detection network using transfer and incremental ensemble learning. This approach is compared to a network trained from scratch, with comparable results observed. This approach demonstrates the feasibility of augmenting networks designed for three-axis CNC machines to five-axis CNC machines.

Keywords: Fault Detection and diagnosis in Manufacturing, Intelligent Process Automation, Data Storage Systems
Abstract: In the realm of manufacturing systems, inferences of failure causes have been performed mainly depending on the reuse of Failure Mode and Effect Analysis (FMEA). However, achieving inference with the same level of quality as experts has been challenging. The objective of this study is to improve the quality of inference by combining maintenance logs and FMEA in the inference of failure causes of manufacturing systems. There are two challenges in using maintenance logs for inference. First, it is difficult to extract causal relationships among failures because the format and quantity of maintenance logs are not consistent. Second, the hierarchy of failures described in each item of maintenance logs is not fixed, making it difficult to search for similar failures by using the items. To address these challenges, we propose a description method for maintenance logs that describes causal relationships among failures and those between failures and functions. We also introduce a failure ontology that represents the hierarchy of failures and conditions impaired by failures based on expert knowledge of manufacturing systems. For the two assumed failures, the inferences derived from maintenance logs and FMEA using the proposed method show better quality than the inferences using FMEA alone. The recall calculated from the failure cause candidates enumerated by experts increased by 3.7 and 5.0 times, respectively.

Keywords: Fault Detection and diagnosis in Manufacturing, Intelligent Process Automation, Mechatronics in Manufacturing Processes
Abstract: This paper focuses on an automatic solution for the detection of manufacturing errors in the context of automatic wiring harness assembly. In the proposed setup, a robot grasp the wires and places them in specific assembly clips according to the wiring harness design. However, due to the deformability of cables, the process outcome is not completely predictable since sometimes the cables remains entangled in other parts of the assembly or do not fit properly into the clips. The proposed error detector verifies the correct insertion of each cables within the clip, considering that the number of cables and their dimension change along the different assembly stage.

The proposed solution covers possible state-of-the-art network learning model that use point clouds as input source, while the network architecture is designed to offer precision and scalability in the context of a flexible and dynamic automation. The developed solution achieved a 96% precision on a dataset composed by various scenario. Therefore, despite being conceived for a robotic wiring harness manufacturing system, the proposed solution can be potentially applied as an online quality control system in manual wiring harness manufacturing.

Keywords: Fault Detection and diagnosis in Manufacturing, Robot Dynamics and Control, Machine Learning
Abstract: In industrial and disaster recovery operations, robot arms take over tasks in hazardous areas. Collision detection methods are essential to prevent damage to the surrounding environment and the robot arm itself. Traditional approaches, such as environmental cameras and tactile sensors, face limitations like installation challenges and high costs. Model-based and data-driven strategies also struggle with accuracy, hindered by external disturbances like friction and the need for extensive data collection. Addressing these challenges, this paper introduces a digital twin-based approach for more accurate collision detection. Digital twins, virtual replicas of physical environments, enable cost-effective and safe data collection. This research utilizes a physical simulator within the digital twin to simulate the efforts of a real robot arm based on the robot’s physical characteristics and motion trajectory, enhancing detection accuracy by adjusting for modeling errors and disturbances through linear regression. Experiments with the xArm 7 robot arm, simulating collisions by applying manual force, demonstrate the proposed method outperformed conventional model-based and machine-learning methods.

Keywords: Fault Detection and diagnosis in Manufacturing, Neural Networks, Hybrid intelligent systems
Abstract: Data-driven fault diagnostics and failure prediction in the industry are dominated by numerical data from sensors. Other data, such as inspection notes, are often discarded due to complexity in feature extraction, fluctuations in information quality, and subjectivity due to human factors. However, for systems where degradation evolves slowly, these data could offer critical insight into the fault diagnostic process. Particularly in the task of quantifying the degradation level of inspected components, the observations made by technicians could hold critical information. Extracting useful information from text data has long remained a challenging task, especially with industrial reports. Therefore, this study presents a method utilizing large language models (LLMs) for extracting machine degradation information from brief on-site technician inspection notes. Industrial proprietary texts serve as background knowledge, with LLMs acting as the embedding medium. The proposed method's performance is investigated through a real industrial case study, where identification of machine degradation level is enhanced using text data and domain knowledge.

Keywords: Fault Detection and diagnosis in Manufacturing, Motion Vibration and Noise Control, Modeling and Design of Mechatonic Systems
Abstract: High voltage circuit breakers (HVCBs) in the gas insulated switch gear (GIS) play an important role in the control and protection of power system. The mechanical faults account for the largest part of common faults in HVCBs. This paper establishes the rigid-flexible model of a 550 kV GIS HVCB, and experimentally studies the behavior characteristics of the HVCB under mechanical fault situation. Firstly, the fine 3D structure model of the 550 kV GIS HVCB is built and the arc-extinguishing principle of the HVCB is analyzed. Then, the rigid model and the rigid-flexible coupling model of the HVCB's components and the whole system are established. The vibration signals of the two models are simulated and compared based on the finite element method. The component model mainly consists of the static arc contact and the dynamic arc contact. Furthermore, the mechanical fault is artificially set in the HVCB, and the vibration waveform are obtained. Finally, the simulation data is compared with the experimental results and the fault characteristics are analyzed. This research realizes the modeling, simulation and measurement of HVCB dynamic characteristics, which is of great significance to the diagnosis and prevention of HVCB mechanical faults.