To address the problem that the number of UAVs is increasing dramatically and the collision risk is increasing dramatically, autonomous collision avoidance and collision avoidance path optimization for conflict risk among multiple UAVs by using genetic algorithms. Under the performance constraints of UAVs, genetic algorithm can realize autonomous collision avoidance of multiple UAVs by using adaptive crossover probability and adaptive mutation probability, and an adaptation function based on the shortest collision avoidance path length and the lowest collision risk. The results of the three-UAVs collision avoidance simulation show that the genetic algorithm can prevent the occurrence of chain collisions while solving the current flight conflict problem and guarantee the safety of UAV flight.


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    Title :

    Study on collision avoidance strategy of multiple UAVs based on genetic algorithm


    Contributors:
    Sun, Shuguang (author) / Dang, Shan (author)

    Conference:

    4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022) ; 2022 ; Guangzhou,China


    Published in:

    Proc. SPIE ; 12257


    Publication date :

    2022-08-01





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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