Force, impedance, and trajectory learning for contact tooling and haptic identification
File(s)Li2018.pdf (1.93 MB)
Accepted version
Author(s)
Type
Journal Article
Abstract
Humans can skilfully use tools and interact with the environment by adapting their movement trajectory, contact force, and impedance. Motivated by the human versatility, we develop here a robot controller that concurrently adapts feedforward force, impedance, and reference trajectory when interacting with an unknown environment. In particular, the robot's reference trajectory is adapted to limit the interaction force and maintain it at a desired level, while feedforward force and impedance adaptation compensates for the interaction with the environment. An analysis of the interaction dynamics using Lyapunov theory yields the conditions for convergence of the closed-loop interaction mediated by this controller. Simulations exhibit adaptive properties similar to human motor adaptation. The implementation of this controller for typical interaction tasks including drilling, cutting, and haptic exploration shows that this controller can outperform conventional controllers in contact tooling.
Date Issued
2018-10-01
Date Acceptance
2018-04-02
Citation
IEEE Transactions on Robotics, 2018, 34 (5), pp.1170-1182
ISSN
1552-3098
Publisher
Institute of Electrical and Electronics Engineers
Start Page
1170
End Page
1182
Journal / Book Title
IEEE Transactions on Robotics
Volume
34
Issue
5
Copyright Statement
© 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.See http://www.ieee.org/publicationsstandards/publications/rights/index.html for more information.
Sponsor
Commission of the European Communities
Commission of the European Communities
Commission of the European Communities
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000446659800003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
231554
PITN-GA-2012-317488
644727
Subjects
Science & Technology
Technology
Robotics
Adaptive control
biological systems control
contact tasks
force control
iterative learning control
robot control
ROBOT MANIPULATORS
UNSTABLE DYNAMICS
ENVIRONMENT
ADAPTATION
TORQUE
Publication Status
Published
Date Publish Online
2018-05-22