A Pesticide Spraying Mission Allocation and Path Planning With Multicopters

被引:1
|
作者
Huang, Jing [1 ,2 ]
Du, Baihui [3 ]
Zhang, Youmin [4 ]
Quan, Quan [5 ]
Wang, Ban [6 ]
Mu, Lingxia [1 ]
机构
[1] Xian Univ Technol, Dept Automat & Informat Engn, Xian 710048, Peoples R China
[2] Jiujiang Precis Test Technol Res Inst, Jiujiang 332000, Peoples R China
[3] China Elect Corp, Beijing 100081, Peoples R China
[4] Concordia Univ, Dept Mech Ind & Aerosp Engn, Montreal, PQ H3G 1M8, Canada
[5] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[6] Northwestern Polytech Univ, Sch Aeronaut, Xian 710072, Peoples R China
基金
中国国家自然科学基金;
关键词
Spraying; Pesticides; Optimization; Task analysis; Resource management; Path planning; Genetic algorithms; Mission assignment; multicopters; multiple traveling salesman problem (mTSP); path planning; point cloud; precision spraying; TRAVELING SALESMAN PROBLEM; UNMANNED AERIAL VEHICLES; ALGORITHM; DEPOT; OPTIMIZATION; FORMULATIONS; TECHNOLOGIES; ASSIGNMENT; SEARCH; SOLVE;
D O I
10.1109/TAES.2024.3355028
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
This article presents a mission allocation and path-planning solution for the pesticide spraying mission of dense trees in hilly terrains using cooperative multicopters. The problem is formulated as a single-depot single-end multiple traveling salesman problem (mTSP). Three different algorithms, namely classical mTSP algorithm, Grouping-TSP combined algorithm, and Grouping-TSP decoupled algorithm, are developed to solve the proposed mTSP. Simulation results indicate that the classical mTSP algorithm provides an evenly distributed task allocation while the Grouping-TSP combined algorithm delivers the optimal solution. In addition, the Grouping-TSP decoupled algorithm minimizes computational complexity. Both Grouping-TSP algorithms integrate a subregions segmentation process to guarantee collision avoidance between the multicopters.
引用
收藏
页码:2277 / 2291
页数:15
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