Single Leg Operational Space Control of Quadruped Robot based on Reinforcement Learning

被引：0

作者：

Rao, Jinhui ^{[1
]}

An, Honglei ^{[1
]}

Zhang, Taihui ^{[1
]}

Chen, Yangzhen ^{[1
]}

Ma, Hongxu ^{[1
]}

机构：

[1] Natl Univ Def Technol, Coll Mechatron Engn & Automat, Changsha 410073, Hunan, Peoples R China

来源：

2016 IEEE CHINESE GUIDANCE, NAVIGATION AND CONTROL CONFERENCE (CGNCC) | 2016年

基金：

中国国家自然科学基金;

关键词：

MANIPULATORS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Due to the strongly environmental adaptation, quadruped robot becomes a research hot spot. The single leg control lays foundation for the control of quadruped robot. The operational space control which is used in the quadruped robot single leg control algorithms usually strongly depends on the accuracy of the model. This paper applies RBF (radial basis function) neural network adaptive control on the single leg, and a kind of control parameters adjustment method which is based on reinforcement learning is proposed. The result shows the algorithm effectively improves the control accuracy and convergence speed under the high-dynamic condition.

引用

页码：597 / 602

页数：6

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