基于遗传算法的无人机最优避撞路径研究

孙淑光; 党杉

doi:doi:10.3969/j.issn.1671-637x.2023.08.010

电光与控制, 2023, 30 (8): 56, 网络出版: 2024-01-17

基于遗传算法的无人机最优避撞路径研究

Optimal Collision Avoidance Path of UAVs Based on Genetic Algorithm

论文大纲

孙淑光党杉

作者单位

中国民航大学电子信息与自动化学院,天津 300000

无人机自主避撞遗传算法 UAV autonomous collision avoidance genetic algorithm ADS-B ADS-B

摘要

针对无人机数量急剧增多、碰撞风险急剧增加的问题, 借助广播式自动相关监视系统(ADS-B)提供的位置、速度信息进行碰撞风险监测, 利用遗传算法实现无人机的自主避撞及避撞路径寻优。避撞策略综合考虑无人机性能约束、ADS-B参数的可信度及无人机飞行环境, 构建多约束参量的适应度函数, 进行多维度的最优避撞路径计算。针对双机和多机避撞情况, 进行无人机避撞仿真, 仿真结果表明, 遗传算法可以在实现无人机自主避撞的同时有效优化避撞路径。

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.

参考文献

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孙淑光, 党杉. 基于遗传算法的无人机最优避撞路径研究[J]. 电光与控制, 2023, 30(8): 56. 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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