In recent years, with the rapid development of UAV technology, the demand of anti-UAV technology is increasingly urgent. Among the existing soft and hard means to counter the attack of UAV swarm, countering UAV swarm by UAV swarm is an important way to counter the attack of UAV swarm in the future. Based on the idea of UAVs intelligent attack and defense confrontation, this paper establishes a simulation environment of UAVs confrontation and a intelligent model of UAV swarm based on MADDPG algorithm. Aiming at the problems such as the speed control of UAV is not accurate and it is difficult to choose the appropriate attack angle in the confrontation, a rule-coupled method is proposed to effectively improve the confront ability of UAV. The experimental results show that the rule-coupled method can significantly improve the winning rate of the UAV swarm in the confrontation from 63% to 81%, and reduce the average epochs required to destroy all the enemy UAVs in a winning game from 61 to 49.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Research on UAV Swarm Confrontation Task Based on MADDPG Algorithm


    Beteiligte:
    Xiang, Lei (Autor:in) / Xie, Tao (Autor:in)


    Erscheinungsdatum :

    2020-12-01


    Format / Umfang :

    671952 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Research on autonomous formation of Multi-UAV based on MADDPG algorithm

    Zhang, Yaozhong / Wu, Zhuoran / Ma, Yunhong et al. | IEEE | 2022


    Pulse type track pursuit game method based on PRD-MADDPG algorithm

    ZHAO LIRAN / DANG CHAOHUI / TANG SHENGYONG et al. | Europäisches Patentamt | 2022

    Freier Zugriff

    Research on Adaptive Grouping Method Under Multi-constraints Swarm Confrontation

    Yin, Hao / Su, Heng / Huang, Tianyu et al. | Springer Verlag | 2022