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IEEE Workshop on Advanced robotics and its Social Impacts, ARSO

作者： Yuwei Du Xin Zhang Mattia Leonori Pietro Balatti Jing Jin Qiang Wang Arash Ajoudani Department of Control Science and Engineering School of Astronautics Harbin Institute of Technology Heilongjiang China Human-Robot Interfaces and Interaction (HRI2) Lab Istituto Italiano di Tecnologia Genova Italy State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

Cooperative human-robot systems are the key technology to improve efficiency in agile production. In this work, a novel on-shoulder supernumerary robotic limb (SRL) is developed for human-robot collaboration. The SRL system is mainly composed of a 6-degree-of-freedom (DoF) lightweight robotic arm and a wearable and adjustable base, which allows different users to regulate the arm installation position to fit their physical dimensions and expand their workspace. As the SRL is close to the human head, nullspace-based collision avoidance is designed to achieve safe motion planning. Meanwhile, a Kalman filter is designed to actively predict human hand position and yield anticipatory motion control of our SRL in handover tasks. Furthermore, we conduct a bi-directional handover case study to verify the capability of the SRL system and the effectiveness of the proposed collaborative handover. The result shows that our control method can guarantee intuitive and natural handover behavior.

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Human-like Walking of a Biped Robot Actuated by Pneumatic Artificial Muscles and Springs*

Human-like Walking of a Biped Robot Actuated by Pneumatic Ar...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Yixiang Liu Qing Bi Xizhe Zang Yibin Li School of Control Science and Engineering Shandong University Jinan China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan China Shandong Institute of Advanced Technology Chinese Academy of Sciences Jinan China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

Human walking gait is much more natural looking and energy efficient compared with biped robots. This paper presents a bio-inspired approach to realizing more human-like biped robotic walking. For this purpose, a biped robot actuated coordinately by pneumatic artificial muscles and springs is developed, capable of exploiting passive compliance of the mechanical system in locomotion. And a control scheme for human-like walking is designed based on finite state machine. Experiments show that the biped robot can walk stably on the treadmill even with some small obstacles. The realized gait has the important features of human walking, including heel strike and toe off, stretched knees, and variation in the height of the body's center of mass, which demonstrates the effectiveness of the proposed approach.

关键词： Conferences Automation Computer aided software engineering

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Position control of X-Y Precision Motion Stage Based on Iterative Learning and Model Prediction

Position Control of X-Y Precision Motion Stage Based on Iter...

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Chinese control and Decision Conference, CCDC

作者： Guopeng Zhang Tao Zhang Qingxin Li Li Chen Hualiang Zhang Jingzhe Fang Yiqiang Zhang School of Artificial Intelligence Shenyang University of Technology Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Artificial Intelligence Shenyang University of Technology Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

The X-Y precision planar motion stage is a highly advanced motion control device that has been widely utilized in various precision motion control fields. This platform achieves precise positioning and control of objects through precise motion along the X and Y axes, providing an outstanding solution for scientific research, industrial production, and other applications. The X-Y platform consists of two permanent magnet synchronous linear motors. In the three-loop control of the motor, when the current loop uses a PID controller, there is a problem in tuning the parameters. This paper replaces the original PID controller in the current loop with a model predictive controller. Simultaneously, addressing the issue of improving the tracking accuracy of the X-Y precision planar motion stage, a forgetting high-order variable gain PD-type iterative learning control is proposed. Subsequently, both of these control methods are applied to the Simulink model of the X-Y precision motion stage motor. This not only solves the complex problem of tuning the motor current loop parameters but also improves the tracking accuracy of the X-Y precision motion stage. The results indicate that when using both model predictive controllers and forgetting high-order variable gain PD-type iterative learning controllers for motor control, not only can the tuning of current loop parameters be omitted, but also tracking errors can be effectively reduced, and the system convergence speed can be accelerated.

关键词： Tracking loops Trajectory tracking Predictive models Motors Mathematical models Motion control Tuning

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Whole-Body Real-Time Motion Planning for Multicopters

Whole-Body Real-Time Motion Planning for Multicopters

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IEEE International Conference on robotics and Automation (ICRA)

作者： Shaohui Yang Botao He Zhepei Wang Chao Xu Fei Gao State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden School of Automation Nanjing Institute of Technology Nanjing China Huzhou Institute Zhejiang University Huzhou China

Multicopters are able to perform high maneuverability yet their potential have not been fully achieved. In this work, we propose a full-body, optimization-based motion planning framework that takes shape and attitude of aerial robot into consideration such that the aggressiveness of drone maneuvering improves significantly in cluttered environment. Our method takes in a series of intersecting polyhedrons that describe a range of 3D free spaces and outputs a time-indexed trajectory in real-time with full-body collision-free guarantee. The drone is modeled as a tilted cuboid, yet we argue that our framework can be freely adjusted to fit multicopters of different shapes. Guaranteeing dynamic feasibility and safety conditions, our framework transforms the original constrained nonlinear programming problem to an unconstrained one in higher dimensions which is further solved by quasi-Newton methods. Benchmark has shown that our method improves the state-of-art with orders of magnitude in terms of computation time and memory usage. Simulations and onboard experiments are carried out as validation.

关键词： Three-dimensional displays Shape Transforms Real-time systems Planning Trajectory Safety

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Review on image edge detection technologies

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Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) 2011年第SUPPL. 1期42卷 811-816页

作者： Wang, Min-Jie Yang, Tang-Wen Han, Jian-Da Qin, Yong Institute of Information Science Beijing Jiaotong University Beijing 100044 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Acad. of Sci. Shenyang 110016 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China

Edge detection is one of the most fundamental topics in the research area of image processing and analysis. First, several classical edge detection methods were introduced, and the performance of these methods was compared;then, several edge detection methods developed in the latest years were reviewed;finally, the trend of the research of the image edge detection in the future was discussed.

关键词： Edge detection

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Research on the application of WIA industrial wireless technology in the substation auxiliary control system

Research on the application of WIA industrial wireless techn...

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Chinese control Conference (CCC)

作者： Ting Yuan Shijie Cui Qingqi Zhao Zhijun Shang Peng Zeng Qiang Gao Ping Li Tao Wang Gang Wang State Grid Liaoning Electric Power Company Limited Panjin Power Supply Company Panjin China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Liaoning CN Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China State Grid Liaoning Electric Power Supply CO. Ltd. Shenyang China State Grid Liaoning Electric Power Company Limited Electric Power Research Institute Shenyang China

This paper presents a new substation auxiliary control system communication scheme based on WIA industrial wireless technology. The structure and operation principle are introduced, and the technical difficulties and solutions of the WIA industrial wireless technology in substation auxiliary control system application are analyzed from the network protocol and hardware design. The validity of the schema has been verified through the practical application in the pilot project.

关键词： Substations control systems Wireless communication Wireless sensor networks Monitoring Temperature sensors Interference

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Neural Network Tracking of Switched Robotic Manipulators with Mode-Dependent Average Dwell Time

Neural Network Tracking of Switched Robotic Manipulators wit...

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

作者： Chao Ma Wei Wu Yidao Ji Wei Wang School of Mechanical Engineering University of Science and Technology Beijing Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

This paper is concerned with the tracking control for robotic manipulators with switching loads and parameter uncertainties. More precisely, the neural network approximation method is adopted with adaptive control to deal with the unmodeled dynamics. Multiple Lyapunov function method is used based on mode-dependent average dwell time, such that the tracking error can converge with desired region. A numerical example is finally provided for illustrating our proposed tracking strategy.

关键词： Switches Robots Manipulators Neural networks control systems Manipulator dynamics Uncertain systems

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The Quality Evaluation of Academic Papers in Carbon Capture, Utilization, and Storage

The Quality Evaluation of Academic Papers in Carbon Capture,...

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Machine Learning, control, and robotics (MLCR), International Conference on

作者： Hangyue Zhang Jie Bai School of Computer Science and Technology Sun Yat-sen University Guangzhou P. R. China City State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing P. R. China

ISBN: (纸本)9781665454605

Carbon capture, utilization, and storage (CCUS) technology is a research hotspot worldwide owing to global climate change and warm gas control. CCUS papers from the last twenty years, derived from the Web of Science database, were analyzed to investigate the impact and citation of academic papers using machine learning methods. Firstly, nine author characteristics, keywords, and three other categories were extracted from the literature. Then, the natural logarithm distribution of the annual average number of citations was obtained, and five evaluation grades were decided based on the citations. Next, the keyword evolution of papers in the CCUS field is analyzed, and a model on the keyword evolution trend index is proposed. Data integration and imbalance processing were conducted after random sampling. A citation prediction model was proposed to evaluate the quality of CCUS academic papers and was verified on the recent five years' CCUS papers by comparing it with nine other mainstream machine learning models. The results indicate that the random forest model exhibits the best performance, with an accuracy rate reaching 88.7%; an ablation experiment was also conducted using the same algorithm. The results prove the effectiveness of our proposed method, shedding light on the quality of academic papers and technology development in CCUS.

关键词： Machine learning Climate change Random forests Modeling Energy storage

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Neural-based Inverse Kinematical Analysis for Bio-inspired Cable-driven Robotic Manipulator

Neural-based Inverse Kinematical Analysis for Bio-inspired C...

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

作者： Hang Fu Yang Liu Wei Wu Xiaoqing Li School of Mechanical Engineering University of Science and Technology Beijing Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

In this paper, the inverse kinematical analysis problem is investigated for a class of bio-inspired cable-driven robotic manipulator. Moreover, the modeling of the redundant cable-driven robotic manipulator is performed. In particular, the RBF neural network is adopted to deal with the unmodeled parameters uncertainties such that the inverse kinematic analysis precision can be improved. In the end, an illustrative example is presented for showing the usefulness of the developed analysis approach.

关键词： Manipulators Clustering algorithms Entropy Robot kinematics Kinematics Training Radial basis function networks

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Leg hybrid rehabilitation based on hip-knee exoskeleton and ankle motion induced by FES

Leg hybrid rehabilitation based on hip-knee exoskeleton and ...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Xikai Tu Jian Huang Jiping He Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China School of Biological and Health Systems Engineering Arizona State University Tempe AZ USA School of Mechatronic Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9781509033652

To regain mobility, stroke patients need to receive repetitive and intensive therapy. Robot-assisted rehabilitation is an active area of research. Cheap robotic leg rehabilitation devices should be developed to meet the demands and assist most patients. A low cost hip-knee exoskeleton prototype powered by pneumatic muscles was developed. On this basis, Functional Electrical Stimulation (FES) induced paralyzed muscles to realize ankle joint rehabilitation training. As both of pneumatic muscle and FES induced muscle possess highly nonlinear characteristics, a sliding control algorithm called Chattering mitigation Robust Variable control (CRVC) was applied to leg hybrid rehabilitation. The combination of exoskeleton and FES is a promising way to reduce the cost and the complexity of designing hip-knee-ankle exoskeleton. The proposed hybrid method is verified by treadmill-based gait training experiments.

关键词： Muscles Exoskeletons Mathematical model Legged locomotion Iron Training

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