Multi-UAV autonomous formation task is one of the important research hotspots in UAV application. A typical mission scenario is constructed for the autonomous formation, maintenance and obstacle avoidance tasks of multi-UAV. Based on Multiple-Agents Deep Deterministic Policy Gradient (MADDPG) algorithm, we designed a hybrid reward distribution mechanism for autonomous formation task, which effectively solved the problem of uneven global reward distribution and individual "selfish strategy", and designed a dynamic communication strategy inside the UAV formation to reduce the computational complexity. It can effectively improve the communication efficiency between UAVs. After training, the UAV can effectively avoid the no-fly zone and efficiently perform autonomous formation flight task. The introduction of the hybrid reward mechanism improves the stability of the UAV autonomous formation task and has certain application prospects.


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    Title :

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


    Contributors:
    Zhang, Yaozhong (author) / Wu, Zhuoran (author) / Ma, Yunhong (author) / Sun, Ruiyang (author) / Xu, Zixiang (author)


    Publication date :

    2022-06-27


    Size :

    1264178 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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