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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Shi, Qiuyu Zhao, Xuan Liao, Haisu Lin, Yongji Huang, Ruisen Wu, Xinyu Gao, Fei Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Shatin 999077 Hong Kong

ISBN: (纸本)9798350325706

Magnetorheological (MR) fluids-based devices such as MR dampers and brakes can output a continuously controllable damping force via modulating the magnitude of the applied magnetic field. Owing to low energy consumption and fast response, recently vast MR dampers and brakes are widely studied and explored for lower limb prostheses and exoskeletons. This paper proposed a novel MR brake with adjustable interdigitated comb for lower limb prostheses. Through actively adjusting the area the of the comb engagement, the maximum viscous and field-induced damping torque can be increased or decreased. Because of that, the dynamic adjustment interval of the output damping torque can be increased to meet the function requirements of the prosthetic knee in different walking modes. Magnetic analysis via ANSYS is performed to check the magnetic density of the MR fluid under different excitations. Mathematical models of the damping torque are built. Finally, a prototype of the novel MR brake is fabricated. © 2023 IEEE.

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Design of Gravity Compensation Scheme for Passive Lifting Method of Multi-degree Freedom Robotic Arm

Design of Gravity Compensation Scheme for Passive Lifting Me...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Jing Sun Chaoran Wei Haotai Chen Bin Wang Xingguang Li Qiang Zhang Space Drive and Manipulation Mechanism Laboratory Beijing Institute of Control Engineering Beijing China Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin China

Before launching a spacecraft, it is necessary to undergo micro low gravity simulations on the ground to test its reliability. The lifting method is not limited by movement time and space, and can simulate long-term low gravity environments. However, the degree of freedom of spatial mechanisms is gradually increasing, and the motion is becoming increasingly complex, making traditional lifting methods unable to meet the needs. In response to the above issues, a lifting gravity simulation scheme for a multi degree of freedom robotic arm that can achieve complex motion is proposed. The design adopts a single sling combined with a hanger to avoid interference during the motion process. Finally, simulation and experiments have proven the feasibility of the scheme - it can achieve efficient unloading without affecting the normal movement of the equipment.

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Model-Based Shape Estimation and Closed-Loop Control of Magnetic Continuum Robot Based on Monocular Vision

Model-Based Shape Estimation and Closed-Loop Control of Magn...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Zhu, Junfeng Huang, Yuanrui Chen, Jian Liu, Hongbin School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100049 China Hong Kong Institute of Science Innovation Chinese Academy of Sciences Centre of AI and Robotics China School of Biomedical Engineering and Imaging Sciences King's College London United Kingdom

ISBN: (纸本)9781665481090

Magnetic continuum robots (MCRs) show promising potential for applications in narrow lumens, such as vascular interventions. Accurate shape sensing of these robots is crucial for the success of interventional surgeries. However, the submillimeter dimensions of MCRs poses significant challenges for integrating additional sensors. An alternative approach is shape estimation from images, yet the lack of precise MCR kinematics can make this process time-consuming. In this work, we propose a novel MCR design featuring a rectangular tip capable of specific planar bending, along with a corresponding kinematic model and a mechanical model. Additionally, we introduce a model-based shape estimation method that enables the estimation of the MCR's shape from a single-view image without the need for external markers. Experimental results demonstrate that our method can estimate an MCR's shape with a mean absolute error (MAE) of 0.58 ± 0.41 mm within 85ms, facilitating real-time application. Furthermore, closed-loop control based on this method has achieved an end position error below 11% of the tip's total length, highlighting the accuracy and practicality of our approach for surgical interventions. © 2024 IEEE.

关键词： Closed loop control systems

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Image Feature Matching Based on Spatial Constraints and Inertial Assistance for AGV Navigation in Digital Workshops 12

Image Feature Matching Based on Spatial Constraints and Iner...

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12th International Conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2022

作者： Sun, Shijie Chen, Li Liang, Wei An, Haibo Zhang, Yinlong School of Artificial Intelligence Shenyang University of Technology Shenyang110020 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Science and Technology on Information Systems Engineering Laboratory The 28th Research Institute of Cetc Jiangsu Nanjing210007 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

VSLAM shows promising potential for AGV navigation in digital workshops, thanks to its merits in low cost, easy configuration, high flexibility, and high accuracy. However, the AGV visual perception system could be easily affected by lighting changes, and body abrupt motions. The state-of-the-art visual feature matching methods may fail to fulfill the navigation tasks in presence of these challenging issues. In order to solve these problems, we propose a feature matching method based on feature space constraints and inertial assistance. In order to reduce the computational time, the spatial constraints are designed to delete the obvious false matches. Besides, the Inertia Assistance Visual Sample Consensus (IAVSAC) is proposed to reduce the computational time in discriminating the wrong feature matches. In order to ensure the reliability of the inertial data, the analysis of IMU noise has been performed. The best IMU configuration with the smallest noises is designed. Our proposed method has been evaluated on the developed AGV navigation platform. The results show that the feature matching accuracy rate and computational time of ours are more favorable than those of RANSAC and MSAC. © 2022 IEEE.

关键词： Navigation

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Instant Motion Recognition of Lower Limb Using Surface Electromyography Signal Based on Convolutional Neural Network

Instant Motion Recognition of Lower Limb Using Surface Elect...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Li, Xiaohui Yu, Xiaoyue Zhou, Hao Jin, Dingxun Li, Guanglin Wang, Lin CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems China University of Chinese Academy of Sciences China Shenzhen Lower Limb Rehabilitation Intelligent Aids Engineering Research Center China Shenzhen Technology University China Southern University of Science and Technology China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society China

ISBN: (纸本)9781665481090

The field of rehabilitation robotics has emerged as a prominent area of research in the medical community in recent years, offering innovative and promising solutions for patients with physical disabilities. The existing lower limb rehabilitation robots have some shortcomings in human-machine compatibility and motion synergy due to the limitation of the real-time human motion intention recognition. In this paper, an instant motion recognition of the lower limb was proposed using surface electromyography (sEMG) for significantly shortening the time delay between the robot motion and the actual human motion. The first 200ms data of the complete sEMG signal for a single motion cycle was employed in the recognition algorithm. The proposed recognition algorithm demonstrated superior accuracy compared to traditional machine learning methods. The accuracy of 9-class recognition was 94.32%, while 12-class recognition achieved that of 89.32%. A data augmentation method based on magnitude warping followed by shifting was employed to enhance recognition accuracy by 11.37% in 9-class recognition and 19.23% in 12-class recognition when comparing with no augmentation. The optimal results for motion recognition were observed when the first 200ms data of the complete sEMG signal for a single motion cycle with a duration of 1.0s were utilized, as evidenced by comparative results. The proposed method offers a novel approach to enhancing human-machine compatibility and comfort in the application of lower limb rehabilitation robots in the future. © 2024 IEEE.

关键词： Convolutional neural networks

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Evaluation of a Weather Plugin in Gazebo: A Case-Study of a Wind Influence on PX4-Based UAV Performance 9th

Evaluation of a Weather Plugin in Gazebo: A Case-Study of a ...

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9th International Conference on Interactive Collaborative robotics, ICR 2024

作者： Imamov, Niyaz Abbyasov, Bulat Tsoy, Tatyana Martínez-García, Edgar A. Magid, Evgeni Laboratory of Intelligent Robotic Systems Intelligent Robotics Department Institute of Information Technology and Intelligent Systems Kazan Federal University 35 Kremlyovskaya St. Kazan420111 Russia Tikhonov Moscow Institute of Electronics and Mathematics HSE University Tallinn Street 34 Moscow Russia Institute of Engineering and Technology Department of Industrial Engineering and Manufacturing Autonomous University of Ciudad Juarez Manuel Díaz H. No. 518-B Zona Pronaf Condominio Chihuahua Cuidad Juárez32315 Mexico

ISBN: (纸本)9783031713590

Unmanned aerial vehicles (UAVs) are utilized in a wide range of real-world applications including search and rescue missions, 3D mapping, building inspection and reconstruction. In a real-world environment, severe weather conditions significantly impact UAV operations. Wind is one of the most dangerous weather factors that can destabilize and even destroy a UAV. Preparing UAV flight algorithms for real-world conditions in order to minimize risks of damage and malfunctioning is a crucial part of a UAV system development. This paper analyses a wind influence on UAV virtual model performance within the Gazebo simulator. The paper focuses on gazebo_wind_plugin package used for creating a windy virtual environment. PX4-LIRS package is used for simulating a UAV within the Gazebo. Three types of experiments were run to evaluate capabilities of the plugin to simulate typical issues that arise in real-world scenarios: a UAV wind resistance, a wind effect on a UAV tilt angle and on a flight velocity. Virtual experiments demonstrated that gazebo_wind_plugin could serve for PX4 UAV flight scenarios modeling in Gazebo simulation with a satisfactory level of realism. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Unmanned aerial vehicles (UAV)

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Energy-Consumption Optimization Control for Lunar Rover's Travel with Torque-Distribution-strategy in Rear Wheels

Energy-Consumption Optimization Control for Lunar Rover's Tr...

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IEEE International Conference on Control Science and systems engineering (CCSSE)

作者： Delun Li Jianfei Cao Yiliang Chen Zongwu Xie State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering Beijing China

ISBN: (数字)9798331517199

ISBN: (纸本)9798331517205

In anticipation of future extensive lunar surface operations, lunar rovers are required to advance towards higher speeds and improved energy conservation. When traveling at high speeds on the lunar surface, the vehicle's energy expenditure is greatly amplified by the influence of the terrain, particularly in conditions where driving and steering are coupled. This paper proposes an energy-saving control strategy for lunar rovers that employs dynamic rear-axle torque distribution, with the goal of optimizing transient energy consumption during travel. To tackle the challenge of non-differentiable functions within the optimization objectives, we suggest using a zeroth-order gradient optimization method for resolution, dynamically constraining the range of control parameters to fulfill the dynamic torque distribution objectives as needed for the task. The energy-saving control effectiveness of the algorithm has been confirmed through simulation, demonstrating a minimum energy-saving ratio of at least 4%, which increases to over 11% as the speed level rises, offering a valuable technical solution for the energy optimization of lunar rovers.

关键词： Space vehicles Energy consumption Torque Distribution strategy Moon Wheels Optimization methods systems engineering and theory Vehicle dynamics Transient analysis

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A Transferability Metric Using Scene Similarity and Local Map Observation for DRL Navigation

arXiv

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arXiv 2023年

作者： Lian, Shiwei Zhang, Feitian The Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China The Department of Advanced Manufacturing and Robotics The State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing100871 China

While deep reinforcement learning (DRL) has attracted a rapidly growing interest in solving the problem of navigation without global maps, DRL typically leads to a mediocre navigation performance in practice due to the gap between the training scene and the actual test scene. To quantify the transferability of a DRL agent between the training and test scenes, this paper proposes a new transferability metric - the scene similarity calculated using an improved image template matching algorithm. Specifically, two transferability performance indicators are designed including the global scene similarity that evaluates the overall robustness of a DRL algorithm and the local scene similarity that serves as a safety measure when a DRL agent is deployed without a global map. In addition, this paper proposes the use of a local map that fuses 2D LiDAR data with spatial information of both the agent and the destination as the DRL observation, aiming to improve the transferability of DRL navigation algorithms. With a wheeled robot as the case study platform, both simulation and real-world experiments are conducted in a total of 26 different scenes. The experimental results affirm the robustness of the local map observation design and demonstrate the strong correlation between the scene similarity metric and the success rate of DRL navigation algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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Dynamic Task Space Control Enables Soft Manipulators to Perform Real-World Tasks

arXiv

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arXiv 2022年

作者： Fischer, Oliver Toshimitsu, Yasunori Kazemipour, Amirhossein Katzschmann, Robert K. Department of Mechanical and Process Engineering Soft Robotics Laboratory Institute of Robotics and Intelligent Systems ETH Zurich Zurich8092 Switzerland

Dynamic motions are a key feature of robotic arms, enabling them to perform tasks quickly and efficiently. A majority of real-world soft robots rely on a quasistatic control approach, without taking dynamic characteristics into consideration. As a result, robots with this restriction move slowly and are not able to adequately deal with forces, such as handling unexpected perturbations or manipulating objects. A dynamic approach to control and modeling would allow soft robots to move faster and handle external forces more efficiently. In previous studies, different aspects of modeling, dynamic control, and physical implementation have been examined separately, while their combination has yet to be thoroughly investigated. Herein, the accuracy of the dynamic model of the multisegment continuum robot is improved by adding new elements that include variable stiffness and actuation behavior. Then, this improved model is integrated with state-of-the-art system identification and dynamic task space control and experiments are performed to validate this combination on a real-world manipulator. As a means of encouraging future research on dynamic control for soft robotic manipulators, the source code is made available for modeling, control, and system identification, along with the recipes for fabricating the manipulator. © 2022, CC BY.

关键词： Religious buildings

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Environmental Recognition and Multimode Continuous-Phase Control for a Powered Transfemoral Prosthesis

Environmental Recognition and Multimode Continuous-Phase Con...

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IEEE International Conference on Development and Learning, ICDL

作者： Shucong Yin Xinxing Chen Teng Ma Yuxuan Wang Yixuan Guo Yuquan Leng Chenglong Fu Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China Department of Biomedical Engineering National University of Singapore.

The continuous-phase-based control method is currently being developed for powered transfemoral prostheses. However, most of the research concentrates on single locomotion mode. The multimode continuous-phase control method for powered transfemoral prostheses is still an open question. To solve the existing problem, this paper proposes a multimode continuous-phase control method for powered transfemoral prostheses. The prosthesis first needs to recognize the surrounding environment and obtain the corresponding environmental features. Then, the gait phase is estimated by phase variable which represents the mapping relationship between thigh angle and gait phase. Finally, the desired trajectories of the knee and ankle joints on various locomotion modes are constructed as functions of the gait phase and environmental features. These functions are called virtual constraints. The proposed phase variable and virtual constraints are evaluated on a public dataset through offline analysis. The root mean squared errors (RMSEs) of the phase variable and virtual constraints in all locomotion modes are less than 3 % and 4 %, respectively. It proves that the proposed method can precisely predict the gait phase and joints angle for powered prostheses in all locomotion modes.

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