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14th IEEE International Conference on Cyber Technology in Automation, Control, and intelligent systems, CYBER 2024

作者： Shen, Yan Dang, Yu Jiang, Tianyu Huo, Weiguang Yu, Ningbo Han, Jianda College of Artificial Intelligence Nankai University Tianjin300350 China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen China Department of Rehabilitation Medicine The Second Medical Center Chinese PLA General Hospital Beijing100853 China National Clinical Research Center for Geriatric Diseases Beijing100853 China National Key Laboratory of Kidney Diseases Beijing100853 China

ISBN: (纸本)9798331506056

Stroke is a disease with a very high mortality rate, and most patients will experience upper limb dysfunction after the disease. Traditional solutions, commonly rigid exoskeletons, have been explored extensively but often fall short due to safety concerns, discomfort, and potential for skin damage owing to their hard attachment mechanisms. To overcome these limitations, this article proposes a textile pneumatic soft suit for elbow joint rehabilitation. This soft suit consists of a modular pneumatic actuator that can help patients with elbow joint flexion and extension rehabilitation training. The design principle is based on the deformation of the textile-based pneumatic bag. The actuator is made of flexible fabric sheets of woven nylon with thermoplastic polyurethane (TPU) coating and 3D printing technology. A mathematical model was developed to describe the relationship between flexion angle and cable length, which could guide the design of the actuator. Experimental validation involved both static and dynamic assessments, confirming the soft suit's capability to meet the requirements of torque and range of the motions. The actuator can provide a starting torque of 7.18 Nm under a pressure of 160 kPa. The suit can provide a range of flexion motion of over 100° for a 1650 g forearm. In the future, we will conduct modeling and further experimental verification of the robot system to complete its control. © 2024 IEEE.

关键词： Pneumatic actuators

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F2A2: flexible fully-decentralized approximate actor-critic for cooperative multi-agent reinforcement learning

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2023年第1期24卷 8447-8521页

作者： Wenhao Li Bo Jin Xiangfeng Wang Junchi Yan Hongyuan Zha School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China School of Software Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China School of Computer Science and Technology Key Laboratory of Mathematics and Engineering Applications Ministry of Education East China Normal University Shanghai China Department of Computer Science and Engineering Key Laboratory of Artificial Intelligence Ministry of Education Shanghai Jiao Tong University Shanghai China

Traditional centralized multi-agent reinforcement learning (MARL) algorithms are sometimes unpractical in complicated applications due to non-interactivity between agents, the curse of dimensionality, and computation complexity. Hence, several decentralized MARL algorithms are motivated. However, existing decentralized methods only handle the fully cooperative setting where massive information needs to be transmitted in training. The block coordinate gradient descent scheme they used for successive independent actor and critic steps can simplify the calculation, but it causes serious bias. This paper proposes a exible fully decentralized actor-critic MARL framework, which can combine most of the actor-critic methods and handle large-scale general cooperative multi-agent settings. A primal-dual hybrid gradient descent type algorithm framework is designed to learn individual agents separately for decentralization. From the perspective of each agent, policy improvement and value evaluation are jointly optimized, which can stabilize multi-agent policy learning. Furthermore, the proposed framework can achieve scalability and stability for the large-scale environment. This framework also reduces information transmission by the parameter sharing mechanism and novel modeling-other-agents methods based on theory-of-mind and online supervised learning. Sufficient experiments in cooperative Multi-agent Particle Environment and StarCraft II show that the proposed decentralized MARL instantiation algorithms perform competitively against conventional centralized and decentralized methods.

关键词： cooperative MARL decentralized actor-critic primal-dual method

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A Robust Visual SLAM System for Small-Scale Quadruped Robots in Dynamic Environments

A Robust Visual SLAM System for Small-Scale Quadruped Robots...

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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Chengyang Li Yulai Zhang Zhiqiang Yu Xinming Liu Qing Shi Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing School of Medical Technology Beijing Institute of Technology Jiaxing China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing China Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper presents a robust visual SLAM system designed for small-scale quadruped robots (ViQu-SLAM) for accurate localization, especially to mitigate the issue of erroneous data association caused by moving objects in dynamic environments. The proposed approach leverages a selfadaptive framework that integrates semantic segmentation with alterations in the spatial location of categorized map points. Besides, combination of leg odometry derived from forward kinematics with IMU provides scale information for positional transformations between keyframes, thus optimizing the overall localization accuracy of quadruped robots. At last, we performed evaluation across various stages and the results demonstrate competitive performance, with 53.16% reduction in average absolute trajectory error compared to that of ORB-SLAM3 in dynamic benchmark datasets. As a result, ViQu-SLAM, including visual and IMU-fused leg odometry, exhibits promising results on a small quadruped robot, reducing positioning errors in dynamic scenes by an average of 29.36% compared to existing state-of-the-art methods.

关键词： Legged locomotion Location awareness Visualization Simultaneous localization and mapping Accuracy Semantic segmentation Heuristic algorithms Object detection Quadrupedal robots Odometry

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A Learning Human-Based Method For Peg-In-Hole Assembly Using ELM

A Learning Human-Based Method For Peg-In-Hole Assembly Using...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Juyi Sheng Sheng Liu Bing Zhu Chi Zhu Yongsheng Ou Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China Maebashi Institute of Technology Japan Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems (#2019B121205007)

This paper focuses on using sensor information to adjust the position for assembly in the presence of uncertainty error in vision. Firstly, a human demonstration of the peg-in-hole assembly is provided, and the data is collected for the next step of training. We start with a human demonstration and collect training data. A network is trained with 6D Force/Torque sensor (F/T sensor) as input and a strategy of which direction the robot end-effector needs to move as output. An algorithm using Extreme Learning Machines (ELM) search is proposed. This is a human-like method of searching for holes. We validated the effectiveness of our method on a KUKA iiwa 7 robot arm.

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Variation of sEMG with Muscle Fatigue for Lower Limb Stroke Patient During Walking

Variation of sEMG with Muscle Fatigue for Lower Limb Stroke ...

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IEEE International Conference on robotics and biomimetics

作者： Wenze Shang Ruisen Huang Wei-Hsin Liao Xinyu Wu Fei Gao Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

sEMG signal is widely used and explored in control strategies of powered assistive human-robot interaction systems due to its non-invasive nature and ability to estimate motion intention well. However, prolonged use of the sEMG-based systems leads to muscle fatigue, contributing to unstable sEMG signals and regarding the performance of sEMG-based control strategies. In this study, three subjects, including two healthy subjects and one stroke subject, participated in our experiment, and the time domain, frequency domain, and complex features extracted from their $sEMG$ signals were utilized to evaluate muscle fatigue. The results indicate that $sEMG$ from the stroke side of the stroke subject contains more non-linear and chaotic parts, and the statistical differences between different trials are more significant, indicating that stroke has a more significant impact on the stroke side of the stroke subject. This study suggests that RMS in the stroke side of stroke subjects is less than that in others, whereas FuzzyEn in the stroke side of stroke subjects is greater than that in others, indicating that stroke leads to different motion patterns and more susceptibility to muscle fatigue.

关键词： Legged locomotion Limbs Frequency-domain analysis biomimetics Human-robot interaction Muscles Fatigue Feature extraction Time-domain analysis Robots

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PhaPaM: In Vitro Panoramic Map Using Phase Correlation

PhaPaM: In Vitro Panoramic Map Using Phase Correlation

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Chinese Control Conference (CCC)

作者： Jie Li Zizhen Li Xin Zhao Tianjin Key Laboratory of Intelligent Robotic (tjKLIR) Institute of Robotics and Automatic Information System (IRAIS) Nankai University Tianjin P. R. China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen P. R. China

Studying cells of brain slices under microscopes reveals subtle changes in neuron networks. But the field of view of microscopes is compromised by high-resolution imaging. A post hoc computer vision-aid process can address the problem. Commonly, feature-based stitching methods can be used to obtain large-scale images. They detect and match salient features within an image. However, the success rate of stitching is highly related to the scale of overlapping of two images and feature-rich properties. Unlike the feature-based methods, this paper reports on a method using a Fourier-based domain, PhaPaM, which infers relative motion from a pair of microscopy images by phase correlation. Specifically, we first apply the Fourier transform for microscope images to sequentially estimate the relative movement of an image pair. Then, we use a minimal spanning tree algorithm to minimize the stitching error and obtain the best stitching path. Finally, we apply the liner-blending method to smoothing the panoramic image. This method is evaluated using large-scale images obtained from the visual cortex of rodent animals, which shows great fidelity and satisfying results.

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Design and 3D Printing of Lower Limb Prosthetic Socket *

Design and 3D Printing of Lower Limb Prosthetic Socket *

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IEEE International Conference on Cyborg and Bionic systems (CBS)

作者： Sheng Li Bin Xie Ye Chen Xinyu Wu Guoxin Fang Yan Zhang Fei Gao Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Shien-Ming Wu School of Intelligent Engineering South China University of Technology Guangzhou China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China State Key Laboratory of Powder Metallurgy Central South University Changsha Hunan China

ISBN: (数字)9798350388039

ISBN: (纸本)9798350388046

The prosthetic socket is a crucial interface connecting the residual limb to the prosthetic device, significantly affecting force transmission and wearer comfort. This work presents a comprehensive framework for design, simulation, and fabrication of the prosthetic socket. A 3D model of the residual limb, including the skeleton model and skin contour, is reconstructed from CT scan data. Using this model, the prosthetic socket and liner are designed based on biomechanical principles. The interaction force between the residual limb and the prosthetic socket and liner is simulated via finite element analysis (FEA) when the body weight of a below-knee amputee exerts on the prosthetic socket. Finally, the prosthetic socket and residual limb are fabricated using additive manufacturing (AM) technology, and a soft prosthetic liner is made of ethylene-vinyl-acetate (EVA) polymer. Clinical trials on a below-knee amputee were conducted to preliminarily test the prosthetic socket’s performance.

关键词： Limbs Solid modeling Sockets Biological system modeling Force Three-dimensional printing Skin Data models Finite element analysis Prosthetics

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Lateral Walking Gait Phase Detection with Data Optimization for a Hip Exoskeleton in Resistance Exercise

Lateral Walking Gait Phase Detection with Data Optimization ...

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IEEE Workshop on Advanced robotics and its Social Impacts, ARSO

作者： Wujing Cao Xinbo Zhu Rui Xu Changyu Li Hongliu Yu Mingming Zhang Haoyong Yu Worawarit Kobsiriphat Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society and SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems. College of Automation Engineering Nanjing University of Aeronautics and Astronautics Jining Zhongke Intelligent Technology Co. Ltd. University of Shanghai for Science and Technology Southern University of Science and Technology Department of Biomedical Engineering National University of Singapore. National Metal and Materials Technology Center Thailand

ISBN: (数字)9798350344639

ISBN: (纸本)9798350344646

The accurate detection of lateral walking gait phases is essential for the effective implementation of hip exoskeleton systems in lateral resistance walking exercises. However, limitations in hardware, such as memory and computing power, in the microcontrollers of wearable devices, significantly impact the size and training speed of the lateral walking gait phase detection model, thus affecting the exoskeleton system. This study proposes a data optimization algorithm that utilizes K-means clustering combined with commonly used machine learning algorithms, including Random Forests (RF), Support Vector Machines (SVM), and k-Nearest Neighbors (KNN), to reduce both the training time and size of the model. With the implementation of this algorithm, the training time and model size of RF, SVM, and KNN-based models are reduced by 89.6%, 99.8%, and 97.9%, and 89.6%, 92.7%, and 95.2% respectively. The corresponding gait phase prediction accuracy experiences only a slight decrease of 1.6%, 1.7%, and 2.8% respectively. This method ensures a sufficiently high accuracy in detecting lateral walking gait phases while simultaneously achieving higher efficiency and a smaller model size.

关键词： Legged locomotion Training Support vector machines Solid modeling Machine learning algorithms Accuracy Exoskeletons

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A Thermoplastic Elastomer Belt Based Robotic Gripper

A Thermoplastic Elastomer Belt Based Robotic Gripper

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2020 IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Xingwen Zheng Ningzhe Hou Pascal Johannes Daniël Dinjens Ruifeng Wang Chengyang Dong Guangming Xie State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China The University of Manchester Manchester United Kingdom Fontys University of Applied Sciences Eindhoven The Netherlands Institute of Ocean Research Peking University Beijing China Peng Cheng Laboratory Shenzhen China

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

Novel robotic grippers have captured increasing interests recently because of their abilities to adapt to varieties of circumstances and their powerful functionalities. Differing from traditional gripper with mechanical components-made fingers, novel robotic grippers are typically made of novel structures and materials, using a novel manufacturing process. In this paper, a novel robotic gripper with external frame and internal thermoplastic elastomer belt-made net is proposed. The gripper grasps objects using the friction between the net and objects. It has the ability of adaptive gripping through flexible contact surface. Stress simulation has been used to explore the regularity between the normal stress on the net and the deformation of the net. Experiments are conducted on a variety of objects to measure the force needed to reliably grip and hold the object. Test results show that the gripper can successfully grip objects with varying shape, dimensions, and textures. It is promising that the gripper can be used for grasping fragile objects in the industry or out in the field, and also grasping the marine organisms without hurting them.

关键词： Shape Service robots Grasping Grippers Stress Surface treatment Strain

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Robotic dual-arm patch clamp for neuron excitability research under mechanical stimulation

Robotic dual-arm patch clamp for neuron excitability researc...

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第43届中国控制会议

作者： Biting Ma Chaoyu Cui Ruimin Li Minghui Li Jinyu Qiu Ke Li Mingzhu Sun Xin Zhao Qili Zhao National Key Laboratory of Intelligent Tracking and Forecasting fo Infectious Diseases Engineering Research Center of Trusted BehaviorIntelligence Ministry of Education Tianjin Key Laboratory of intelligentRobotic (tikLIR) Institute of Robotics and Automatic Information System(IRAlS) Nankai University Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The dual-arm patch clamp technique, using one micropipette electrode to patch the target cell to record its electric signals with the other micropipette mechanically stimulating the target cell, is a significant technique in neuroscience for studying neuron excitability under mechanical stimulation. A key step for dual-arm patch clamp operation is to coordinate two micropipettes to reach the target cells in the narrow brain tissue environment. The traditional manual operations face issues such as inaccurate workspace estimation, clumsy movements, and collision risks of the two micropipettes, resulting in low operational efficiency. Addressing the above issues, a robotic dual-arm patch clamp method was developed for neuron excitability research under mechanical stimulation in this paper. First, the reachable workspace of the dual-arm was calculated based on a kinematics model. Then, a robotic dual arm patch clamp operation procedure is proposed to approach, whole-cell patch, and mechanically stimulate the target cell. The experiment results on neurons in mouse brain slices show that the success rate of dual micropipette contacting cell surface reaches up to 90%(18/20) at an average speed of 6 mins/cell, which are both significantly improved in comparison to manual operation. An increase in neuron excitability in the primary visual cortex(V1) was found under the mechanical stimulation, proving the feasibility of the proposed system for studying the impact of mechanical stimulation on ion channel activities.

关键词： Robotic Patch Clamp Robotic Cell Measurement Workspace Calculation Whole-cell Recording Mechanical Stimulation

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