This paper proposed an autonomous intelligent decision-making method, which can be used to evade the attack of multi-interceptors. A self-learning model based on MADDPG algorithm is established with four engines of a spacecraft as multi-agent system. The model takes the relative distance and the total maneuvering time as variables to design the evaluation function. A simulation environment is constructed with four interceptors intercepting a spacecraft at the same time. The autonomous evasion impulse maneuvers of the spacecraft are realized by training. Compared with the random evasion maneuvers method, this autonomous maneuvers method improves the success probability of escape by nearly 30%. This research provides a valuable theoretical method for modern space operations.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Reinforcement Learning Based Spacecraft Autonomous Evasive Maneuvers Method Against Multi-interceptors


    Contributors:
    Zhao, Yu (author) / Zhou, Ding (author) / Bai, Chengchao (author) / Zheng, Hongxing (author) / Guo, Jifeng (author)


    Publication date :

    2020-11-27


    Size :

    450834 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Minimum impulse orbital evasive maneuvers

    BURK, ROGER C. / WIDHALM, JOSEPH W. | AIAA | 1989


    Autonomous evasive maneuvers triggered by infrastructure-based detection of pedestrian intentions

    Kohler, Sebastian / Schreiner, Brian / Ronalter, Steffen et al. | IEEE | 2013


    Optimal Multiple-Impulse Satellite Evasive Maneuvers

    Prussing, J.E. | Online Contents | 1994


    Safety Verification of Autonomous Vehicles for Coordinated Evasive Maneuvers

    Althoff, Matthias / Althoff, Daniel / Wollherr, Dirk et al. | Tema Archive | 2010