Redundant robot control with learning from expert demonstrations

被引：1

作者：

Ramirez, Jorge ^{[1
]}

Yu, Wen ^{[2
]}

机构：

[1] Natl Polytech Inst, Dept Control Automat, IPN, CINVESTAV, Mexico City, DF, Mexico

[2] IPN, Dept Control Automat, CINVESTAV, Mexico City, DF, Mexico

来源：

2022 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI) | 2022年

关键词：

reinforcement learning; learning from expert demonstration; redundant robot control;

D O I：

10.1109/SSCI51031.2022.10022138

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a biased exploration based reinforcement learning, which uses expert experiences to avoid the exploration of all states. The method is applied to control redundant robots with expert experiences. A 7-degree-of-freedom robot manipulator is used in experiments. The results show that expert demonstrations based robot control works well.

引用

页码：715 / 720

页数：6

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