Adaptive Optimal Control for Redundantly Actuated Arms

  • Djordje Mitrovic
  • Stefan Klanke
  • Sethu Vijayakumar
Conference paper

DOI: 10.1007/978-3-540-69134-1_10

Volume 5040 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Mitrovic D., Klanke S., Vijayakumar S. (2008) Adaptive Optimal Control for Redundantly Actuated Arms. In: Asada M., Hallam J.C.T., Meyer JA., Tani J. (eds) From Animals to Animats 10. SAB 2008. Lecture Notes in Computer Science, vol 5040. Springer, Berlin, Heidelberg

Abstract

Optimal feedback control has been proposed as an attractive movement generation strategy in goal reaching tasks for anthropomorphic manipulator systems. Recent developments, such as the iterative Linear Quadratic Gaussian (iLQG) algorithm, have focused on the case of non-linear, but still analytically available, dynamics. For realistic control systems, however, the dynamics may often be unknown, difficult to estimate, or subject to frequent systematic changes. In this paper, we combine the iLQG framework with learning the forward dynamics for a simulated arm with two limbs and six antagonistic muscles, and we demonstrate how our approach can compensate for complex dynamic perturbations in an online fashion.

Keywords

Adaptive optimal control learning dynamics redundant actuation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Djordje Mitrovic
    • 1
  • Stefan Klanke
    • 1
  • Sethu Vijayakumar
    • 1
  1. 1.Institute of Perception, Action & BehaviorUniversity of EdinburghEdinburghUnited Kingdom