Novel Stable Walking for Humanoid Robot Using Particle Swarm Optimization Algorithm

DOI

10.2991/aiie-15.2015.90How to use a DOI?

Keywords

PSO; walking robot; learning time; walking speed

Abstract

This paper describes a novel walking gait generation algorithm based on inverse kinematics for a biped robot. The proposed algorithm uses the PSO (Particle Swarm Optimization) algorithm in order to find optimized values for the five walking algorithm parameters. The proposed experiment approach is tested on a small-sized humanoid robot in the DCSELAB, VNU-HCM. Simulation and experimental results reveal that using the PSO algorithm with an efficient fitness function can significantly reduce learning time. Moreover, a considerable fast walking speed is achieved.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - T.T. Huan
AU  - H.P.H. Anh
PY  - 2015/07
DA  - 2015/07
TI  - Novel Stable Walking for Humanoid Robot Using Particle Swarm Optimization Algorithm
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 322
EP  - 325
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.90
DO  - 10.2991/aiie-15.2015.90
ID  - Huan2015/07
ER  -