Reinforcement Learning-Based Continuous Action Space Path Planning Method for Mobile Robots
A reinforcement learning-based continuous action space path planning method for mobile robots is proposed in this article. First, the kinematic model of the mobile robot is analyzed, and on this basis, the optimal state space is constructed according to the minimum depth of the field value in the de...
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| Main Authors: | Weimin Zhang, Guoyong Wang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2022/9069283 |
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