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Application of the “Alliance Algorithm” to Energy Constrained Gait Optimization

  • Valerio Lattarulo
  • Sander G. van Dijk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7416)

Abstract

This paper deals with the problem of energy constrained gait optimization for bipedal walking. We present a solution to this problem obtained by applying a recently introduced heuristic method, the Alliance Algorithm (AA), and compare its performance against a Genetic Algorithm (GA). We show experimentally that the intrinsic ability of the AA to handle hard constraints enables it to find solutions significantly better than the GA. Also with the constraint removed the AA show more reliable optimization results. Finally, we show that the final gait obtained through this method outperforms most solutions to this problem presented in previous works, in terms of walking speed.

Keywords

Genetic Algorithm Particle Swarm Optimization Solution Space Central Pattern Generator Hard Constraint 
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 2012

Authors and Affiliations

  • Valerio Lattarulo
    • 1
  • Sander G. van Dijk
    • 1
  1. 1.Adaptive Systems Research GroupUniversity of HertfordshireHatfieldUK

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