Variable Impedance Control and Learning—A Review
Robots that physically interact with their surroundings, in order to accomplish some tasks or assist humans in their activities, require to exploit contact forces in a safe and proficient manner. Impedance control is considered as a prominent approach in robotics to avoid large impact forces while o...
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| Vydáno v: | Frontiers in robotics and AI Ročník 7; s. 590681 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Switzerland
Frontiers Media S.A
21.12.2020
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| Témata: | |
| ISSN: | 2296-9144, 2296-9144 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Robots that physically interact with their surroundings, in order to accomplish some tasks or assist humans in their activities, require to exploit contact forces in a safe and proficient manner. Impedance control is considered as a prominent approach in robotics to avoid large impact forces while operating in unstructured environments. In such environments, the conditions under which the interaction occurs may significantly vary during the task execution. This demands robots to be endowed with online adaptation capabilities to cope with sudden and unexpected changes in the environment. In this context, variable impedance control arises as a powerful tool to modulate the robot's behavior in response to variations in its surroundings. In this survey, we present the state-of-the-art of approaches devoted to variable impedance control from control and learning perspectives (separately and jointly). Moreover, we propose a new taxonomy for mechanical impedance based on variability, learning, and control. The objective of this survey is to put together the concepts and efforts that have been done so far in this field, and to describe advantages and disadvantages of each approach. The survey concludes with open issues in the field and an envisioned framework that may potentially solve them. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 Reviewed by: Sunan Huang, National University of Singapore, Singapore; Riccardo Muradore, University of Verona, Italy This article was submitted to Robotic Control Systems, a section of the journal Frontiers in Robotics and AI Edited by: Yongping Pan, National University of Singapore, Singapore |
| ISSN: | 2296-9144 2296-9144 |
| DOI: | 10.3389/frobt.2020.590681 |