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.


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    Title :

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


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Lee, Sangchul (editor) / Han, Cheolheui (editor) / Choi, Jeong-Yeol (editor) / Kim, Seungkeun (editor) / Kim, Jeong Ho (editor) / Wang, Weixiang (author) / Zhang, An (author) / Bi, Wenhao (author) / Mao, Zeming (author) / Li, Minghao (author)

    Conference:

    Asia-Pacific International Symposium on Aerospace Technology ; 2021 ; Korea (Republic of) November 15, 2021 - November 17, 2021



    Publication date :

    2022-09-30


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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