基于ACO的无人机巡线路径规划研究
Ant Colony Optimization Algorithm Based Path Planning Research for UAV Power Line Inspection
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摘要: 无人机巡线的推广和应用使得带电维护和检修成为可能,从而提高了电力工人的维护和检修速度。由此,合理地、精细化地规划无人机巡线路径已成为亟待解决的问题。该文以无人机巡线路径作为研究对象,首先,针对无人机巡检路径的规划特点,建立无人机巡线作业环境模型;然后,建立能耗最低、可巡线时间最长的目标函数,并利用蚁群算法对其进行求解,以优化巡线目标的拍摄地点和巡线路径;最后,利用GPS定位功能实现无人机自动巡线功能,建立无人机巡线指挥系统。算例仿真和实际使用情况表明,利用文中提出的算法,可以在确保无人机完成巡检任务的前提下,缩短巡检路径、减少所需采集照片的数量,并在提高了巡检工作效率的同时,减少了所需分析图片的数量。Abstract: The promotion and application of the UAV line patrol has made live power maintenance & repair possible,and has materially improved the maintenance and repair speed.Therefore,planning the UAV portal route in a reasonable and refine way has become an urgent issue to be addressed. This paper deals with the route of the UAV patrol. First,according to the characteristics of the UAV patrol path planning, the environment model of UAV patrol operation is established;second, the objective function with the lowest energy consumption and the longest patrol time is established,and the ant colony algorithm is used to solve it,and the shooting point and route of the target are optimized; finally, the GPS positioning function is used to realize the function of UAV automatic line patrol,and the command system of UAV line patrol is established. The simulation results show that the proposed algorithm can shorten the inspection path,reduce the number of photos to be collected, improve the inspection efficiency and reduce the number of photos to be analyzed.