Motion Planning for Humanoid Robot Based on Hybrid Evolutionary Algorithm | Zendy

Qiubo Zhong | Zendy; Songhao Piao | Zendy; Chao Gao | Zendy

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Motion Planning for Humanoid Robot Based on Hybrid Evolutionary Algorithm

Author(s) -

Qiubo Zhong,

Songhao Piao,

Chao Gao

Publication year - 2010

Publication title -

international journal of advanced robotic systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.394

H-Index - 46

eISSN - 1729-8814

pISSN - 1729-8806

DOI - 10.5772/9703

Subject(s) - computer science , humanoid robot , trajectory , robot , artificial neural network , process (computing) , gait , particle swarm optimization , artificial intelligence , movement (music) , motion planning , evolutionary algorithm , motion (physics) , stability (learning theory) , computer vision , simulation , algorithm , machine learning , physiology , philosophy , physics , aesthetics , astronomy , biology , operating system

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

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