摘要
覆盖路径规划广泛应用于环境清洁、建图、监控等场景,为了提高覆盖效率,经验证,一组有自主运动能力的无人飞行器配合机载传感器可以提供有效帮助.本文提出一种可以应用于大规模复杂环境的多无人飞行器覆盖路径规划方法.在面积规模大、环境情况复杂的区域内,计算出可以采集到精确可靠环境信息的最优覆盖路径是比较困难的,本文提出的覆盖路径规划方法基于分块优化的思想,将大规模的环境分成若干面积较小的子区域,分别计算子区域内的局部最优覆盖路径,在一些特定的约束条件下,所有子区域内的局部覆盖路径可以连接成一条遍历环境中每个子区域的整体覆盖路径,兼顾了环境的差异性和覆盖的完整性.同时,为了保证整体路径的平滑,适合飞行器跟踪,在规划路径时还考虑到减小相邻两段局部路径之间的过度转角和飞行器完成一次环境覆盖的调头转向次数,通过设计不同的覆盖模式以及在计算局部路径的评价函数中加入转角相关项来实现路径的平滑.最后,通过仿真和实验验证了所提算法的有效性和可行性.
Route planning coverage is commonly used in vacuuming,mapping,and tracking of the area.A group of programmable unmanned aerial vehicles(UAVs)is an ideal choice for such missions to increase coverage efficiency.In this paper,for the large-scale environmental coverage challenge,a novel route planning approach is proposed,which gathers abundant information per unit length and ensures full coverage for the entire environment.The proposed approach is based on the method of section optimization,as it is extremely difficult to obtain a coverage route directly for the large-scale setting with accurate and reliable information.Next,the atmosphere is divided into several small sub-regions that conform to the sensor’s detection distance.Based on this,the optimal coverage route for each sub-region is calculated.For clarity,the route in each sub-region is termed as a partial path.Under certain specific constraints,the obtained partial routes are connected to constitute an integral path.It is worth noting that the higher steering frequency and the greater turning angle will result in more time and energy consumption.The proposed approach is also aimed at reducing these two significant indexes.Another benefit of the proposed approach is that even if the area in charge is changed,it is easy to adjust.To validate the performance of the proposed planning scheme,simulation,and experimental results are provided.
作者
肖玉婷
方勇纯
梁潇
林河
何桢
XIAO YuTing;FANG YongChun;LIANG Xiao;LIN He;HE Zhen(Tianjin Key Laboratory of Intelligent Robotics,Institute of Robotics and Automatic Information System,Nankai University,Tianjin 300350,China)
出处
《中国科学：技术科学》
EI
CSCD
北大核心
2020年第4期439-452,共14页
Scientia Sinica(Technologica)
基金
国家自然科学基金(批准号:61903200,61873132)
天津市自然科学基金(编号:19JCQNJC03500,16JCZDJC30300)资助项目。
关键词
分块优化
多无人机
环境覆盖
路径规划
section optimization
multiple UAVs
environment coverage
route planning
