基于遗传算法的无人机监视覆盖航路规划算法研究
Research on Algorithm of UAV Monitoring Coverage Path Planning Based on Genetic Algorithm

DOI: 10.12677/CSA.2019.96135, PP. 1208-1215

Keywords: 遗传算法，人工势场法，无人机，监视覆盖航路规划
Genetic Algorithm, Artificial Potential Field Method, Drone, Surveillance Coverage Route Planning

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Abstract:

为解决传统覆盖航路规划算法结果样式单一、对抗性环境下灵活性差的问题，提出了基于遗传算法的监视覆盖航路规划算法，生成样式多样、监视任务执行中对抗性好的监视覆盖航路。在人工势场法的基础上，将激发势场的种子编码为二元组串形式的基因，通过交叉、变异、合并等算子的操作增加种子样式的多样性，从而规划出转弯少、监视时间间隔短、对抗性好的监视覆盖航路。最后通过算例对算法进行了验证，结果表明算法有效地满足了监视任务覆盖航路规划的需求。
In order to solve the problem that the traditional coverage route planning algorithm has a single style and poor flexibility in the confrontation environment, a genetic algorithm-based surveillance coverage route planning algorithm is proposed to generate a variety of surveillance and coverage routes for monitoring missions. On the basis of the artificial potential field method, the seeds of the excitation potential field are encoded into genes in the form of binary strings, and the diversity of seed patterns is increased by operations such as crossover, mutation, and merging, thereby planning less turning and monitoring. Short time intervals and good confrontation monitoring cover the route. Finally, the algorithm is verified by an example. The results show that the algorithm effectively meets the requirements of monitoring mission coverage route planning.

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