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A new methodology for robot controller design

2005

Conference Paper

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Gauss' principle of least constraint and its generalizations have provided a useful insights for the development of tracking controllers for mechanical systems [1]. Using this concept, we present a novel methodology for the design of a specific class of robot controllers. With our new framework, we demonstrate that well-known and also several novel nonlinear robot control laws can be derived from this generic framework, and show experimental verifications on a Sarcos Master Arm robot for some of these controllers. We believe that the suggested approach unifies and simplifies the design of optimal nonlinear control laws for robots obeying rigid body dynamics equations, both with or without external constraints, holonomic or nonholonomic constraints, with over-actuation or underactuation, as well as open-chain and closed-chain kinematics.

Author(s): Peters, J. and Peters, J. and Mistry, M. and Udwadia, F.
Journal: Proceedings of the 5th ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC‘05)
Volume: 5
Pages: 1067-1076
Year: 2005
Month: September
Day: 0
Publisher: ASME

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

DOI: 10.1115/DETC2005-85166
Event Name: 5th ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC-MSNDC 2005)
Event Place: Long Beach, CA,USA

Address: New York, NY, USA
Digital: 0
ISBN: 0-7918-4743-8
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@inproceedings{5054,
  title = {A new methodology for robot controller design},
  author = {Peters, J. and Peters, J. and Mistry, M. and Udwadia, F.},
  journal = {Proceedings of the 5th ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC‘05)},
  volume = {5},
  pages = {1067-1076 },
  publisher = {ASME},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {New York, NY, USA},
  month = sep,
  year = {2005},
  month_numeric = {9}
}