A Survey of Robot Manipulation Behavior Research Based on Deep Reinforcement Learning

被引：0
|
作者：
Chen J. [1 ]
Zheng M. [1 ,2 ]
机构：
[1] School of Mechanical, Electronic and Control Engineering, Beijing Jiaotong University, Beijing
[2] Key Laboratory of Vehicle Advanced Manufacturing, Measuring and Control Technology (Beijing Jiaotong University), Ministry of Education, Beijing
来源：
Jiqiren/Robot | 2022年 / 44卷 / 02期
关键词：
Deep learning; Deep reinforcement learning; Reinforcement learning; Robot learning; Robot manipulation;
D O I：
10.13973/j.cnki.robot.210008
中图分类号：
学科分类号：
摘要：
By summarizing previous studies, the basic theories and algorithms of deep learning and reinforcement learning are introduced firstly. Secondly, the popular DRL (deep reinforcement learning) algorithms and their applications to robot manipulation are summarized. Finally, the future development directions of applying DRL to robot manipulation are forecasted according to the current problems and possible solutions. © 2022, Science Press. All right reserved.
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页码：236 / 256
页数：20
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