A binary gridding path-planning method for plant-protecting UAVs on irregular fields  

作　　者：XU Wang-ying YU Xiao-bing XUE Xin-yu 

机构地区：[1]School of Management Science and Engineering,Nanjing University of Information Science&Technology,Nanjing 214000,P.R.China [2]Nanjing Institute of Agricultural Mechanization,Ministry of Agriculture and Rural Affairs,Nanjing 214000,P.R.China

出　　处：《Journal of Integrative Agriculture》2023年第9期2796-2809,共14页农业科学学报（英文版）

基　　金：funded by the National Natural Science Foundation of China(72274099 and 71974100);the Humanities and Social Sciences Fund of the Ministry of Education,China(22YJC630144);the Major Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province,China(2019SJZDA039);the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(KYCX22_1244).

摘　　要：The use of plant-protecting unmanned aerial vehicles(UAVs)for pesticide spraying is an essential operation in modern agriculture.The balance between reducing pesticide consumption and energy consumption is a significant focus of current research in the path-planning of plant-protecting UAVs.In this study,we proposed a binarization multi-objective model for the irregular field area,specifically an improved non-dominated sorting genetic algorithm–II based on the knee point and plane measurement(KPPM-NSGA-ii).The binarization multi-objective model is applied to convex polygons,concave polygons and fields with complex terrain.The experiments demonstrated that the proposed KPPM-NSGA-ii can obtain better results than the unplanned path method whether the optimization of pesticide consumption or energy consumption is preferred.Hence,the proposed algorithm can save energy and pesticide usage and improve the efficiency in practical applications.

关 键 词：plant-protecting UAV PATH-PLANNING multi-objective optimization gridization Pareto optimal 

分 类 号：S252.3[农业科学—农业机械化工程]