Dynamic gait pattern generation with reinforcement learning

Date

2005-01-01

Author

Erden, Mustafa Suphi
Leblebicioğlu, Mehmet Kemal

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

Subject Keywords

Gait pattern, Radial basis function neural network, Reinforcement learning, Six-legged robot, Walking

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79960747404&origin=inward
https://hdl.handle.net/11511/102171

Journal

IFAC Proceedings Volumes (IFAC-PapersOnline)

DOI

https://doi.org/10.3182/20050703-6-cz-1902.01295

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

M. S. Erden and M. K. Leblebicioğlu, “Dynamic gait pattern generation with reinforcement learning,” IFAC Proceedings Volumes (IFAC-PapersOnline), vol. 16, pp. 151–156, 2005, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79960747404&origin=inward.