Dynamic gait pattern generation with reinforcement learning

Erden M. S., LEBLEBİCİOĞLU M. K.

IFAC Proceedings Volumes (IFAC-PapersOnline), vol.16, pp.151-156, 2005 (Scopus) identifier

  • Publication Type: Article / Abstract
  • Volume: 16
  • Publication Date: 2005
  • Doi Number: 10.3182/20050703-6-cz-1902.01295
  • Journal Name: IFAC Proceedings Volumes (IFAC-PapersOnline)
  • Journal Indexes: Scopus
  • Page Numbers: pp.151-156
  • Keywords: Gait pattern, Radial basis function neural network, Reinforcement learning, Six-legged robot, Walking
  • Middle East Technical University Affiliated: Yes

Abstract

This paper presents the gait pattern generation work performed for the sixlegged robot EA308 developed in our laboratory. The aim is to achieve a dynamically developing gait pattern generation structure using reinforcement learning. For the six legged robot a simplified simulative model is constructed. The algorithm constructs a radial basis function neural network (RBFNN) to command proper leg configurations to the simulative robot. The weights of the RBFNN are learned using reinforcement learning. The developed structure succeeded in learning gait patterns compatible with different speeds of the robot. Copyright © 2005 IFAC.