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Computing the Optimal Trajectory of Arm Movement: The TOPS (Task Optimization in the Presence of Signal-Dependent Noise) Model

  • Hiroyuki Miyamoto
  • Daniel M. Wolpert
  • Mitsuo Kawato
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 109)

Abstract

A new framework is proposed for motor control: the Task Optimization in the Presence of Signal-dependent noise (TOPS) model. By using this model, we need not specify the position, velocity, and acceleration of the hand at the start and end of a movement. We can easily apply this model to any task setting as well as to simple point-to-point reaching movements. Estimation of the optimal trajectories using computer simulations showed that in the case of a moving target, the trajectories estimated by this model are very different from those estimated by the minimum jerk model.

Keywords

Optimal Trajectory Radial Basis Function Network Goal Area Sigma Point Hand Trajectory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Hiroyuki Miyamoto
    • 1
  • Daniel M. Wolpert
    • 2
  • Mitsuo Kawato
    • 3
  1. 1.Kawato Dynamic Brain ProjectJapan Science and Technology CorporationKyotoJapan
  2. 2.Sobell Department of Neurophysiology, Institute of NeurologyUniversity College LondonLondonUK
  3. 3.ATR Human Information Processing Research LaboratoriesKyotoJapan

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