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Kinematic analysis and position/force control of the anthrobot dextrous hand

IEEE TRANSACTIONS ON systems MAN AND CYBERNETICS PART B-CYBERNETICS 1997年第1期27卷 95-104页

作者： Kyriakopoulos, KJ VanRiper, J Zink, A Stephanou, HE New York State Center for Advanced Technology in Automation and Robotics and Electrical Department of Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

The increasing demand for robotic applications in unstructured environments is motivating the need for dextrous end-effecters which can cope with the wide variety of tasks and objects encountered in these environments, A new anthropomorphic robot hand (Anthrobot) which was designed for these environments is described. In this paper, the problem of developing the kinematics and unit consistent hybrid position/force control of the Anthrobot fingers is considered as the first step toward its utilization for either teleoperation or autonomous operation, A dynamic model of the fingers is identified and used to develop the control laws, The experimental results of applying the control to the Anthrobot are discussed.

关键词： Kinematics Force control Fingers robotics and automation Robots Humans Thumb Anthropomorphism Vehicle dynamics Power system modeling

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Development of micro-and nanorobotics: A review

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Science China(Technological Sciences) 2019年第1期62卷 1-20页

作者： YANG Jia ZHANG Chuang WANG XiaoDong WANG WenXue XI Ning LIU LianQing State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Emerging Technologies Institute Department of Industrial & Manufacturing Systems Engineering University of Hong Kong

Micro-and nanorobotic is an emerging field of research arising from the cross-fusion of micro/nano technology and robotics and has become an important part of robotics. Micro-and nanorobots have the advantages of small size, low weight, large thrust-toweight ratio, high flexibility, and high sensitivity. Due to the characteristics distinguishing from macroscopic robots, micro-and nanorobots have stimulated the research interest of the scientific community and opened up numerous application fields such as drug delivery and disease diagnosis. In the past 30 years, research on micro-and nanorobots has made considerable *** article provides a comprehensive overview of the development of these robots. First, the application of the robots is reviewed. Then, the key components of the robots are discussed separately, covering their actuation, design, fabrication and control. In addition, from the perspectives of intelligence and sensing, clinical applications, materials and performance, the challenges that may be encountered in the development of such robots in the future are discussed. Finally, the entire article is summarized, and concepts for future micro-and nanorobots are described.

关键词： micro-and nanorobots magnetic actuation manipulation biohybrid robot

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Collision Position Sensing for Manipulator Using Force/Torque Sensor 34

Collision Position Sensing for Manipulator Using Force/Torqu...

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第三十四届中国控制会议

作者： LENG Yuquan CHEN Zhengcang ZHANG Wei ZHANG Yang HE Xu LUO Haitao ZHOU Weijia Department of Space Automation Technologies & Systems the State Key Laboratory of RoboticsShenyang Institute of Automation University of Chinese Academy of Science

ISBN: (纸本)9781467374439

Force sensing including collision position, force direction and force size makes robots smoothly interact with environment to strongly adapt to outside world. Skin sensing imitates principle of human skin using special material and physical structure with disadvantages of complex design, low sampling rate, and poor generality and so on. In this paper, the method of using fore/torque sensor to calculate collision position, force direction and force size is provided. We detail elaborate algorithm based on physical principle, and unified modeling method for basic geometric surface. Considering algorithm solvability and uniqueness, three constraints are proposed, which are joint constraint, contour constraint and force direction constraint. In order to solve conflict solution of algorithm in redundant constraints, we propose compatibility and method. In addition, gravity compensation and dynamic compensation are also described for working manipulator in gravity and dynamic environment. As a result of our simulation experiment, we would find that this method is effective for manipulator to measure collision position.

关键词： Collision Position Force/Torque Sensor Skin Sensor Manipulator

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Controlling CAN Servo Step Drives and Their Remote Monitoring by Using Protocol OPC UA

Controlling CAN Servo Step Drives and Their Remote Monitorin...

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2019 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2019

作者： Martinov, G. Issa, A. Martinova, L. Institute of Automation and Robotics Dept. Computer Control Systems Moscow Russia

ISBN: (纸本)9781728100616

The diverse requirements of customers in automation systems increase the need for improved adaptability, flexibility and of simplicity production processes. which creates new horizons for modern production systems. Fortunately, the achievements of the Industry 4.0 (fourth industrial revolution) have provided many solutions to these problems. In this study, an OPC UA-based solution is proposed for monitoring the working process of CAN servo drives. By integrating C++ based OPC UA libraries to implement common OPC UA functionality and developing protocol of interaction between the kernel of CNC system and OPC UA server. The aim of this work is to ensure the connection mechanism between OPC UA Server of CNC system and OPC UA clients which are currently existed on the market. This flexible model allows users to remotely tune and set up CAN servo drives and monitor their work. © 2019 IEEE.

关键词： Digital storage

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Parallel Learning:a Perspective and a Framework

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 389-395页

作者： Li Li Yilun Lin Nanning Zheng Fei-Yue Wang Department of Automation TNListTsinghua University IEEE State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences Institute of Artificial Intelligence and Robotics(IAIR) Xi'an Jiaotong University Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology

The development of machine learning in complex system is hindered by two problems *** first problem is the inefficiency of exploration in state and action space,which leads to the data-hungry of some state-of-art data-driven *** second problem is the lack of a general theory which can be used to analyze and implement a complex learning *** this paper,we proposed a general methods that can address both two *** combine the concepts of descriptive learning,predictive learning,and prescriptive learning into a uniform framework,so as to build a parallel system allowing learning system improved by *** a new perspective of data,knowledge and action,we provide a new methodology called parallel learning to design machine learning system for real-world problems.

关键词： Descriptive learning machine learning parallel learning parallel systems predictive learning prescriptive learning

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Evaluation of a vibrotactile feedback device for spatial guidance

Evaluation of a vibrotactile feedback device for spatial gui...

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2011 IEEE World Haptics Conference, WHC 2011

作者： Weber, Bernhard Schätzle, Simon Hulin, Thomas Preusche, Carsten Deml, Barbara University of Magdeburg Institute of Ergonomics Manufacturing Systems and Automation Germany Institute of Robotics and Mechatronics Germany

ISBN: (纸本)9781457702976

In the present study, a vibrotactile feedback device for spatial guidance was evaluated in a tracking task paradigm. Participants (N = 18) had to translate and rotate virtual objects according to the vibrotactile vs. verbal cues without visual information. Both types of spatial guidance were evaluated using objective performance data (i.e. speed, accuracy) as well as subjective judgments. Results indicate that distinguishing spatial cues during the translational task was more difficult when being guided by vibrotactile feedback compared to verbal feedback. Nevertheless, individuals with vibrotactile guidance showed better performance at rotational tasks. Implications for the further design process and other areas of application are discussed. © 2011 IEEE.

关键词： Accuracy Actuators Analysis of variance Atmospheric measurements Haptic I/O Human Factors Humans Particle measurements Visualization Voice I/O

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Parallel Driving in CPSS:A Unified Approach for Transport automation and Vehicle Intelligence

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IEEE/CAA Journal of Automatica Sinica 2017年第4期4卷 577-587页

作者： Fei-Yue Wang Nan-Ning Zheng Dongpu Cao Clara Marina Martinez Li Li Teng Liu IEEE State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Advanced Vehicle Engineering Center Cranfield University Department of Automation Tsinghua University State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Qingdao Huituo Intelligent Machine Company

The emerging development of connected and automated vehicles imposes a significant challenge on current vehicle control and transportation systems. This paper proposes a novel unified approach, Parallel Driving, a cloud-based cyberphysical-social systems(CPSS) framework aiming at synergizing connected automated driving. This study first introduces the CPSS and ACP-based intelligent machine systems. Then the parallel driving is proposed in the cyber-physical-social space,considering interactions among vehicles, human drivers, and information. Within the framework, parallel testing, parallel learning and parallel reinforcement learning are developed and concisely reviewed. Development on intelligent horizon(iHorizon)and its applications are also presented towards parallel *** proposed parallel driving offers an ample solution for achieving a smooth, safe and efficient cooperation among connected automated vehicles with different levels of automation in future road transportation systems.

关键词： ACP theory connected automated driving cyber-physical-social systems(CPSS) iHorizon parallel driving parallel horizon parallel learning parallel reinforcement learning parallel testing

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Ground condition sensing of a snake-like robot

Ground condition sensing of a snake-like robot

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IEEE International Conference on robotics, Intelligent systems and Signal Processing

作者： Lu, Y Ma, SG Li, B Chen, L Robotics Laboratory Shenyang Institute of Automation CAS China Department of Systems Engineering Ibaraki University Japan

ISBN: (纸本)078037925X

Snake-like robot has its unique locomotion mode and can change its locomotion form while the ground condition changed, to achieve the best velocity and efficiency. We first analyze the snake-like robot locomotion on different terrains simply, then point out the significance to sense the ground status that is the base of choosing different locomotion form on different ground. Last we use force sensors to distinguish the different ground status.

关键词： Robots

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Fatigue Recognition Based on Audiovisual Content 1

Fatigue Recognition Based on Audiovisual Content

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1st International Conference on Control systems, Mathematical Modelling, automation and Energy Efficiency, SUMMA 2019

作者： Malov, Dmitrii Shumskaya, Olga Laboratory of Autonomous Robotics Systems Saint-Petersburg Institute for Isnformatics and Automation Saint-Petersburg Russia

ISBN: (纸本)9781728149110

We analyzed modern approaches to fatigue recognition. Most of the methods are based on classical statistical analysis. Some of the methods are based on machine learning models, in particular artificial neural networks. We have tested independent models for every modality: images and audio and concluded there should be united model for both source of information. © 2019 IEEE.

关键词： Neural networks

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A policy gradient algorithm integrating long and short-term rewards for soft continuum arm control

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Science China(Technological Sciences) 2022年第10期65卷 2409-2419页

作者： DONG Xiang ZHANG Jing CHENG Long XU WenJun SU Hang MEI Tao School of Electrical Engineering and Automation Anhui UniversityHefei 230601China State Key Laboratory for Control and Management of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Robotics Research Center Peng Cheng LaboratoryShenzhen 518055China

The soft continuum arm has extensive application in industrial production and human life due to its superior safety and flexibility. Reinforcement learning is a powerful technique for solving soft arm continuous control problems, which can learn an effective control policy with an unknown system model. However, it is often affected by the high sample complexity and requires huge amounts of data to train, which limits its effectiveness in soft arm control. An improved policy gradient method, policy gradient integrating long and short-term rewards denoted as PGLS, is proposed in this paper to overcome this issue. The shortterm rewards provide more dynamic-aware exploration directions for policy learning and improve the exploration efficiency of the algorithm. PGLS can be integrated into current policy gradient algorithms, such as deep deterministic policy gradient(DDPG). The overall control framework is realized and demonstrated in a dynamics simulation environment. Simulation results show that this approach can effectively control the soft arm to reach and track the targets. Compared with DDPG and other model-free reinforcement learning algorithms, the proposed PGLS algorithm has a great improvement in convergence speed and performance. In addition, a fluid-driven soft manipulator is designed and fabricated in this paper, which can verify the proposed PGLS algorithm in real experiments in the future.

关键词： soft arm control Cosserat rod deep reinforcement learning policy gradient algorithm high sample complexity

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