Disclosed is an intelligent collision avoidance method for a swarm of unmanned surface vehicles based on deep reinforcement learning; firstly, a theoretical framework of autonomous learning collision avoidance of a swarm of unmanned surface vehicles based on deep reinforcement learning is proposed, and the LSTM neural network memory ability is integrated to realize the continuity of collision avoidance actions; then, according to the USV environment in the framework, the characterization method is obtained, and the USV collision avoidance reward and punishment function is proposed to evaluate the collision avoidance effect; finally, an intelligent collision avoidance training system for a swarm of unmanned surface vehicles is formed. The simulation and verification of this disclosure show that the USV trained in this disclosure can navigate safely in the collision avoidance environment with a swarm of unmanned surface vehicles and realize intelligent collision avoidance.


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    Title :

    Intelligent collision avoidance method for a swarm of unmanned surface vehicles based on deep reinforcement learning


    Contributors:
    MA YONG (author) / ZHAO YUJIAO (author) / WANG YULONG (author)

    Publication date :

    2024-05-21


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G05D SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES , Systeme zum Steuern oder Regeln nichtelektrischer veränderlicher Größen / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS