Differential game theory for versatile physical human–robot interaction
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Accepted version
Author(s)
Li, Y
Carboni, G
Gonzalez, F
Campolo, D
Burdet, E
Type
Journal Article
Abstract
The last decades have seen a surge of robots working in contact with humans. However, until now these contact robots have made little use of the opportunities offered by physical interaction and lack a systematic methodology to produce versatile behaviours. Here, we develop an interactive robot controller able to understand the control strategy of the human user and react optimally to their movements. We demonstrate that combining an observer with a differential game theory controller can induce a stable interaction between the two partners, precisely identify each other’s control law, and allow them to successfully perform the task with minimum effort. Simulations and experiments with human subjects demonstrate these properties and illustrate how this controller can induce different representative interaction strategies.
Date Issued
2019-01-07
Date Acceptance
2018-11-27
Citation
Nature Machine Intelligence, 2019, 1 (1), pp.36-43
ISSN
2522-5839
Publisher
Nature Research
Start Page
36
End Page
43
Journal / Book Title
Nature Machine Intelligence
Volume
1
Issue
1
Copyright Statement
© The Author(s), under exclusive licence to Springer Nature Limited 2019
Sponsor
Commission of the European Communities
Engineering & Physical Science Research Council (EPSRC)
Identifier
https://www.nature.com/articles/s42256-018-0010-3
Grant Number
644727
EP/N032772/1
Subjects
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Interdisciplinary Applications
Computer Science
STROKE
COORDINATION
ADAPTATION
MUSCLES
ARM
Publication Status
Published
Date Publish Online
2019-01-07