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Hybrid IDM/Impedance learning in human movements

2001

Conference Paper

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In spite of motor output variability and the delay in the sensori-motor, humans routinely perform intrinsically un- stable tasks. The hybrid IDM/impedance learning con- troller presented in this paper enables skilful performance in strong stable and unstable environments. It consid- ers motor output variability identified from experimen- tal data, and contains two modules concurrently learning the endpoint force and impedance adapted to the envi- ronment. The simulations suggest how humans learn to skillfully perform intrinsically unstable tasks. Testable predictions are proposed.

Author(s): Burdet, E. and Teng, KP. and Chew, CM. and Peters, J. and , BT.
Book Title: ISHF 2001
Journal: Proceedings of the 1st International Symposium on Measurement, Analysis and Modeling of Human Functions (ISHF2001)
Volume: 1
Pages: 1-9
Year: 2001
Month: September
Day: 0

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

Event Name: 1st International Symposium on Measurement, Analysis and Modeling of Human Functions (ISHF2001)
Event Place: Sapporo, Japan

Digital: 0
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@inproceedings{5060,
  title = {Hybrid IDM/Impedance learning in human movements},
  author = {},
  journal = {Proceedings of the 1st International Symposium on Measurement, Analysis and Modeling of Human Functions (ISHF2001)},
  booktitle = {ISHF 2001},
  volume = {1},
  pages = {1-9},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = sep,
  year = {2001},
  month_numeric = {9}
}