Motion Planning for Humanoid Robot Based on Hybrid Evolutionary Algorithm

In this paper, online gait control system is designed for walking-up-stairs movement according to the features of humanoid robot, the hybrid evolutionary approach based on neural network optimized by particle swarm is employed for the offline training of the movement process, and the optimal gait of...

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Bibliographic Details
Main Authors: ZHONG Qiu-bo, PIAO Song-hao, GAO Chao
Format: Article
Language:English
Published: SAGE Publishing 2010-09-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.5772/9703
Description
Summary:In this paper, online gait control system is designed for walking-up-stairs movement according to the features of humanoid robot, the hybrid evolutionary approach based on neural network optimized by particle swarm is employed for the offline training of the movement process, and the optimal gait of the stability is generated. Additionally, through embedded monocular vision, on-site environmental information is collected as neural network input, so necessary joint trajectory is output for the movement. Simulations and experiment testify the efficiency of the method.
ISSN:1729-8814