To overcome the problems of traditional distributed target allocation algorithms in terms of lack of target strategic priority, poor scalability, and robustness, this paper proposes a proximal strategy optimization algorithm that combines threat assessment and attention mechanism (TAPPO). Based on the distributed training framework, the algorithm integrates a threat assessment and dynamic attention strategy and designs a dynamic reward function based on the current hit rate of the drone and the missile benefit ratio to improve the algorithm’s exploration ability and scalability. Through an 8vs8 multi-UAV confrontation experiment in a digital twin simulation environment, the results show that the agent using the TAPPO algorithm for target allocation defeats the state machine with an 85% winning rate and is significantly better than other current mainstream target allocation algorithms, verifying the effectiveness of the algorithm.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Multi-UAV Cooperative Target Assignment Method Based on Reinforcement Learning


    Beteiligte:
    Yunlong Ding (Autor:in) / Minchi Kuang (Autor:in) / Heng Shi (Autor:in) / Jiazhan Gao (Autor:in)


    Erscheinungsdatum :

    2024




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




    Reinforcement-Learning-Based Cooperative Dynamic Weapon-Target Assignment in a Multiagent Engagement

    Merkulov, Gleb / Iceland, Eran / Michaeli, Shay et al. | AIAA | 2025


    Reinforcement Learning Based Decentralized Weapon-Target Assignment and Guidance

    Merkulov, Gleb / Iceland, Eran / Michaeli, Shay et al. | AIAA | 2024


    Dynamic target assignment method based on multi-agent decentralized cooperative auction

    Mo, L. / Zongji, C. | British Library Online Contents | 2007


    UAV Swarm Cooperative Target Search: A Multi-Agent Reinforcement Learning Approach

    Hou, Yukai / Zhao, Jin / Zhang, Rongqing et al. | IEEE | 2024


    Weapon–Target Assignment by Reinforcement Learning with Pointer Network

    Na, Hyungho / Ahn, Jaemyung / Moon, Il-Chul | AIAA | 2023