Hybrid dynamic control algorithm for humanoid robots based on reinforcement learning

被引：14

作者：

Katic, Dusko M. ^{[1
]}

Rodic, Aleksandar D. ^{[1
]}

Vukobratovic, Miomir K. ^{[1
]}

机构：

[1] Mihailo Pupin Inst, Robot Dept, Belgrade 11060, Serbia

来源：

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS | 2008年 / 51卷 / 01期

关键词：

humanoid robots; biped locomotion; integrated dynamic control; reinforcement learning; actor-critic method;

D O I：

10.1007/s10846-007-9174-5

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, hybrid integrated dynamic control algorithm for humanoid locomotion mechanism is presented. The proposed structure of controller involves two feedback loops: model-based dynamic controller including impart-force controller and reinforcement learning feedback controller around zero-moment point. The proposed new reinforcement learning algorithm is based on modified version of actor-critic architecture for dynamic reactive compensation. Simulation experiments were carried out in order to validate the proposed control approach.The obtained simulation results served as the basis for a critical evaluation of the controller performance.

引用

页码：3 / 30

页数：28

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