A Novel UAV Path Planning Method Based on Layered PER-DDQN

Weixiang Wang, An Zhang, Wenhao Bi, Zeming Mao, Minghao Li

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

Path planning is a key technology for Unmanned Aerial Vehicles (UAVs) to complete the operational mission in a complex battlefield environment. A step-by-step path planning method based on the Layered Double Deep Q-Network with Prioritized Experience Replay (Layered PER-DDQN) is proposed in this paper. The novel method is constructed by combining the threat avoidance network and collision-free network based on the PER-DDQN framework. By analyzing the current environment of the UAV, the networks output threat avoidance action vector and obstacle avoidance action vector, and the method does a weighted summation of the action vectors according to the weight of the subproblems to obtain the final action. The simulation experiment verifies that the Layered PER-DDQN path planning method has better convergence and practicability than the Deep Q-Network and A* algorithm.

源语言英语
主期刊名The Proceedings of the 2021 Asia-Pacific International Symposium on Aerospace Technology APISAT 2021, Volume 2
编辑Sangchul Lee, Cheolheui Han, Jeong-Yeol Choi, Seungkeun Kim, Jeong Ho Kim
出版商Springer Science and Business Media Deutschland GmbH
693-702
页数10
ISBN(印刷版)9789811926341
DOI
出版状态已出版 - 2023
活动Asia-Pacific International Symposium on Aerospace Technology, APISAT 2021 - Virtual, Online
期限: 15 11月 202117 11月 2021

出版系列

姓名Lecture Notes in Electrical Engineering
913
ISSN(印刷版)1876-1100
ISSN(电子版)1876-1119

会议

会议Asia-Pacific International Symposium on Aerospace Technology, APISAT 2021
Virtual, Online
时期15/11/2117/11/21

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