environment11oct13.pdf (593.97 kB)
Impedance learning for robots interacting with unknown environments
In this paper, impedance learning is investigated for robots interacting with unknown environments. A twoloop control framework is employed and adaptive control is developed for the inner-loop position control. The environments are described as time-varying systems with unknown parameters in the state-space form. The gradient-following scheme and betterment scheme are employed to obtain a desired impedance model, subject to unknown environments. The desired interaction performance is achieved in the sense that a defined cost function is minimized. Simulation and experiment studies are carried out to verify the validity of the proposed method.
History
Publication status
- Published
File Version
- Accepted version
Journal
IEEE Transactions on Control Systems TechnologyISSN
1063-6536Publisher
Institute of Electrical and Electronics EngineersExternal DOI
Issue
4Volume
22Page range
1422-1432Department affiliated with
- Engineering and Design Publications
Notes
(c) 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2017-12-15First Open Access (FOA) Date
2017-12-15First Compliant Deposit (FCD) Date
2017-12-15Usage metrics
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