Path Planning Algorithm for Plant Protection UAVs in Multiple Operation Areas

被引：0
|
作者：
Xu B. [1 ,2 ]
Chen L. [1 ,3 ]
Xu M. [1 ,3 ]
Tan Y. [2 ]
机构：
[1] Beijing Research Center of Intelligent Equipment for Agriculture, Beijing
[2] College of Engineering, China Agricultural University, Beijing
[3] Beijing Key Laboratory of Intelligent Equipment Technology for Agriculture, Beijing Academy of Agriculture and Forestry, Beijing
来源：
Chen, Liping (chenlp@nercita.org.cn) | 1600年 / Chinese Society of Agricultural Machinery卷 / 48期
关键词：
Algorithm; Multi-area operation; Path planning; Plant protection UAVs;
D O I：
10.6041/j.issn.1000-1298.2017.02.010
中图分类号：
学科分类号：
摘要：
According to multi-area operations, a kind of overall route planning algorithm for plant protection UAVs was developed in order to reduce flight distance in multi-area operations and operating sequence of each area was reasonable allocation to improve operational efficiency and reduce energy consumption of the UAVs. The algorithm was divided into three parts, namely, single area route planning, operating sequences of areas and dispatching route planning among areas. After analyzing a variety of covering operation modes in aspects of operation distance, extra coverage and missed coverage, the UAVs operation mode in single area was determined. Optimized operation sequences of areas were planned based on genetic algorithm and traveling salesman problem (TSP). Dispatching routes among areas were planned based on improved genetic algorithm with binary coding, finally the overall route planning algorithm was achieved. The simulation was performed in an operation of five different irregular areas, numbers of each area were set as A, B, C, D and E. Operation route of each area was planned by using the previously proposed algorithm of route planning algorithm based on operation path angle in irregular, achieving operation start point, end point and node point coordinates of each area. Operation sequences of areas were achieved based on genetic algorithm and TSP, dispatching routes among areas were planned based on the improved genetic algorithm, of which the code was a random five-digit binary sequence, each digit represented arrangement of start point and end point of each area. The simulation result proved feasibility of the multi-area route planning algorithm. Nowadays, unmanned operations becomes trend, this multi-area route planning algorithm not only saves manpower required by route planning, but also makes operation management easier, and it is suitable for autonomous unmanned aerial vehicles and can be widely used in the area of precision agriculture. © 2017, Chinese Society of Agricultural Machinery. All right reserved.
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页码：75 / 81
页数：6
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