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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    Titel :

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


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Lee, Sangchul (Herausgeber:in) / Han, Cheolheui (Herausgeber:in) / Choi, Jeong-Yeol (Herausgeber:in) / Kim, Seungkeun (Herausgeber:in) / Kim, Jeong Ho (Herausgeber:in) / Wang, Weixiang (Autor:in) / Zhang, An (Autor:in) / Bi, Wenhao (Autor:in) / Mao, Zeming (Autor:in) / Li, Minghao (Autor:in)

    Kongress:

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



    Erscheinungsdatum :

    30.09.2022


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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