• Electronics Optics & Control
  • Vol. 30, Issue 8, 56 (2023)
SUN Shuguang and DANG Shan
Author Affiliations
  • [in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2023.08.010 Cite this Article
    SUN Shuguang, DANG Shan. Optimal Collision Avoidance Path of UAVs Based on Genetic Algorithm[J]. Electronics Optics & Control, 2023, 30(8): 56 Copy Citation Text show less

    Abstract

    To solve the problem that the number of UAVs increases sharply and the collision risk increases sharply,the position and velocity information provided by Automatic Dependent Surveillance-Broadcast (ADS-B) is used to monitor the collision risk,and the genetic algorithm is used to realize the autonomous collision avoidance and collision avoidance path optimization of UAVs.The collision avoidance strategy comprehensively considers the UAV performance constraints,the confidence of ADS-B parameters and the UAV flight environment,the fitness function with multi-constraint parameters is constructed for multi-dimensional optimal collision avoidance path calculation.As for the situation of two and multiple UAVs collision avoidance,the UAV collision avoidance simulation is carried out.The simulation results show that the genetic algorithm can effectively optimize the collision avoidance path while achieving autonomous collision avoidance for UAVs.
    SUN Shuguang, DANG Shan. Optimal Collision Avoidance Path of UAVs Based on Genetic Algorithm[J]. Electronics Optics & Control, 2023, 30(8): 56
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