A path planning algorithm for a crop monitoring fixed-wing unmanned aerial system

作     者：Longhao QIAN Yi Lok LO Hugh Hong-tao LIU 

作者机构：Institute of Aerospace Studies University of Toronto Department of Mechanical Engineering The University of Hong Kong 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2024年第67卷第8期

页      面：5-23页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0828[工学-农业工程] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant (Grant No. RGPIN-2023-05148) 5G-Enabled Trustworthy Common Operational Picture with Edge Server Data Engine (5G-TCOP) (Grant No. 10037356 MN3-026) 

主　　题：path planning genetic algorithm energy minimization fixed-wing UAS aerial survey 

摘      要：With the growing demand for automation in agriculture, industries increasingly rely on drones to perform crop monitoring and surveillance. In this regard, fixed-wing unmanned aerial systems(UASs)are viable platforms for scanning a large crop field, given their payload capacity and range. To achieve maximum coverage without landing for battery replacement, an algorithm for producing a minimal required energy survey path is essential. Hence, an energy-aware coverage path planning algorithm is proposed *** constraints for a fixed-wing UAS to fly at low altitudes while achieving full coverage of the crop field are first analyzed. Then, the full path is decomposed into straight-line and U-turn primitives. Finally, an algorithm to calculate a combination of straight-line segments and U-turns is proposed to obtain the path with minimum required energy consumption. The genetic algorithm is used to efficiently determine the order of the straight-line paths to traverse. Case studies show that the proposed algorithm can produce planning results for a convex-polygon-shaped crop field.