Adaptive-Constrained Impedance Control for Human-Robot Co-Transportation
Human-robot co-transportation allows for a human and a robot to perform an object transportation task cooperatively on a shared environment. This range of applications raises a great number of theoretical and practical challenges arising mainly from the unknown human-robot interaction model as well...
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| Published in | IEEE transactions on cybernetics Vol. 52; no. 12; pp. 13237 - 13249 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
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Piscataway
IEEE
01.12.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| Abstract | Human-robot co-transportation allows for a human and a robot to perform an object transportation task cooperatively on a shared environment. This range of applications raises a great number of theoretical and practical challenges arising mainly from the unknown human-robot interaction model as well as from the difficulty of accurately model the robot dynamics. In this article, an adaptive impedance controller for human-robot co-transportation is put forward in task space. Vision and force sensing are employed to obtain the human hand position, and to measure the interaction force between the human and the robot. Using the latest developments in nonlinear control theory, we propose a robot end-effector controller to track the motion of the human partner under actuators' input constraints, unknown initial conditions, and unknown robot dynamics. The proposed adaptive impedance control algorithm offers a safe interaction between the human and the robot and achieves a smooth control behavior along the different phases of the co-transportation task. Simulations and experiments are conducted to illustrate the performance of the proposed techniques in a co-transportation task. |
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| AbstractList | Human–robot co-transportation allows for a human and a robot to perform an object transportation task cooperatively on a shared environment. This range of applications raises a great number of theoretical and practical challenges arising mainly from the unknown human–robot interaction model as well as from the difficulty of accurately model the robot dynamics. In this article, an adaptive impedance controller for human–robot co-transportation is put forward in task space. Vision and force sensing are employed to obtain the human hand position, and to measure the interaction force between the human and the robot. Using the latest developments in nonlinear control theory, we propose a robot end-effector controller to track the motion of the human partner under actuators’ input constraints, unknown initial conditions, and unknown robot dynamics. The proposed adaptive impedance control algorithm offers a safe interaction between the human and the robot and achieves a smooth control behavior along the different phases of the co-transportation task. Simulations and experiments are conducted to illustrate the performance of the proposed techniques in a co-transportation task. Human-robot co-transportation allows for a human and a robot to perform an object transportation task cooperatively on a shared environment. This range of applications raises a great number of theoretical and practical challenges arising mainly from the unknown human-robot interaction model as well as from the difficulty of accurately model the robot dynamics. In this article, an adaptive impedance controller for human-robot co-transportation is put forward in task space. Vision and force sensing are employed to obtain the human hand position, and to measure the interaction force between the human and the robot. Using the latest developments in nonlinear control theory, we propose a robot end-effector controller to track the motion of the human partner under actuators' input constraints, unknown initial conditions, and unknown robot dynamics. The proposed adaptive impedance control algorithm offers a safe interaction between the human and the robot and achieves a smooth control behavior along the different phases of the co-transportation task. Simulations and experiments are conducted to illustrate the performance of the proposed techniques in a co-transportation task.Human-robot co-transportation allows for a human and a robot to perform an object transportation task cooperatively on a shared environment. This range of applications raises a great number of theoretical and practical challenges arising mainly from the unknown human-robot interaction model as well as from the difficulty of accurately model the robot dynamics. In this article, an adaptive impedance controller for human-robot co-transportation is put forward in task space. Vision and force sensing are employed to obtain the human hand position, and to measure the interaction force between the human and the robot. Using the latest developments in nonlinear control theory, we propose a robot end-effector controller to track the motion of the human partner under actuators' input constraints, unknown initial conditions, and unknown robot dynamics. The proposed adaptive impedance control algorithm offers a safe interaction between the human and the robot and achieves a smooth control behavior along the different phases of the co-transportation task. Simulations and experiments are conducted to illustrate the performance of the proposed techniques in a co-transportation task. |
| Author | Yu, Xinbo Cheng, Long Feng, Yanghe Silvestre, Carlos Li, Bin He, Wei |
| Author_xml | – sequence: 1 givenname: Xinbo orcidid: 0000-0003-0958-6020 surname: Yu fullname: Yu, Xinbo organization: Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing, China – sequence: 2 givenname: Bin surname: Li fullname: Li, Bin organization: Institute of Artificial Intelligence and the School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China – sequence: 3 givenname: Wei orcidid: 0000-0002-8944-9861 surname: He fullname: He, Wei email: weihe@ieee.org organization: Institute of Artificial Intelligence and the School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China – sequence: 4 givenname: Yanghe orcidid: 0000-0003-1608-8695 surname: Feng fullname: Feng, Yanghe organization: College of Systems Engineering, National University of Defense Technology, Changsha, China – sequence: 5 givenname: Long orcidid: 0000-0001-7565-8788 surname: Cheng fullname: Cheng, Long organization: State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China – sequence: 6 givenname: Carlos orcidid: 0000-0002-5096-5527 surname: Silvestre fullname: Silvestre, Carlos organization: Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Macau, China |
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| Snippet | Human-robot co-transportation allows for a human and a robot to perform an object transportation task cooperatively on a shared environment. This range of... Human–robot co-transportation allows for a human and a robot to perform an object transportation task cooperatively on a shared environment. This range of... |
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| SubjectTerms | Actuators Adaptive algorithms Adaptive control Collaboration Constraints Control algorithms Control theory Controllers End effectors Error constraint Force Human motion human–robot co-transportation Impedance Initial conditions input constraint Interaction models neural networks (NNs) Nonlinear control Position measurement Robot control Robot dynamics Robot sensing systems Robots Sensors Task analysis Task space Transportation vision and force sensing |
| Title | Adaptive-Constrained Impedance Control for Human-Robot Co-Transportation |
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