Motion planning for humanoid robot based on hybrid evolutionary algorithm

被引：0
|
作者：
Qiu-Bo Z. [1 ,2 ]
Song-Hao P. [1 ]
Chao G. [1 ]
机构：
[1] School of Computer Science and Technology, Harbin Institute of Technology, Harbin
[2] School of Information and Computer Engineering, Norestest Forestry University, Harbin
来源：
International Journal of Advanced Robotic Systems | 2010年 / 7卷 / 03期
关键词：
Gait control; Humanoid robot; Neural network; Particle swarm optimization;
D O I：
10.5772/9703
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
页码：209 / 216
页数：7
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