74844.pdf (863.68 kB)
Force, impedance and trajectory learning for contact tooling and haptic identification
journal contribution
posted on 2023-06-09, 12:44 authored by Yanan LiYanan Li, Gowrishankar Ganesh, Nathanaël Jarrassé, Sami Haddadin, Alin Albu-Schaeffer, Etienne BurdetHumans 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.
History
Publication status
- Published
File Version
- Accepted version
Journal
IEEE Transactions on RoboticsISSN
1552-3098Publisher
Institute of Electrical and Electronics EngineersExternal DOI
Issue
5Volume
34Page range
1170-1182Department affiliated with
- Engineering and Design Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2018-04-05First Open Access (FOA) Date
2018-05-23First Compliant Deposit (FCD) Date
2018-04-05Usage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC