Path Planning Method With Improved Artificial Potential Field—A Reinforcement Learning Perspective

Path Planning Method With Improved Artificial Potential Field—A Reinforcement Learning Perspective

The artificial potential field approach is an efficient path planning method. However, to deal with the local-stable-point problem in complex environments, it needs to modify the potential field and increases the complexity of the algorithm. This study combines improved black-hole potential field an...

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Bibliographic Details
Main Authors: Qingfeng Yao, Zeyu Zheng, Liang Qi, Haitao Yuan, Xiwang Guo, Ming Zhao, Zhi Liu, Tianji Yang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Reinforcement learning
neural network
potential field
path planning
Online Access:https://ieeexplore.ieee.org/document/9146273/

Internet

https://ieeexplore.ieee.org/document/9146273/

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