Deep Reinforcement Learning-based Trajectory Planning for Manipulator Obstacle Avoidance
A deep reinforcement learning (DRL)-based motion planning method is proposed to improve long planning elapse and lengthy path of the traditional planning algorithms for robotic manipulator movement in obstacle avoidance. Firstly, based on the mathematical model of the manipulator and the motion envi...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2023-12-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2023.12.006 |
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