Coverage Path Planning Optimization of Heterogeneous UAVs Group for Precision Agriculture

运动规划 计算机科学 过程(计算) 任务(项目管理) 路径(计算) 集合(抽象数据类型) 遗传算法 实时计算 精准农业 基线(sea) 运筹学 农业 系统工程 人工智能 工程类 机器学习 地理 海洋学 考古 地质学 机器人 程序设计语言 操作系统
作者
Ravil I. Mukhamediev,Kirill Yakunin,Margulan Aubakirov,Ilyas Assanov,Yan Kuchin,Адилхан Сымагулов,Vitaly Levashenko,Elena Zaitseva,Dmitry Sokolov,Yedilkhan Amirgaliyev
出处
期刊:IEEE Access [Institute of Electrical and Electronics Engineers]
卷期号:11: 5789-5803 被引量:53
标识
DOI:10.1109/access.2023.3235207
摘要

Precision farming is one of the ways of transition to the intensive methods of agricultural production. The case of application of unmanned aerial vehicles (UAVs) for solving problems of agriculture and animal husbandry is among the actively studied issues. The UAV is capable of solving the tasks of monitoring, fertilizing, herbicides, etc. However, the effective use of UAV requires to solve the tasks of flight planning, taking into account the heterogeneity of the available attachments and the problem solved in the process of the overflight. This research investigates the problem of flight planning of a group of heterogeneous UAVs applied to solving the issues of coverage, which may arise both in the course of monitoring and in the process of the implementation of agrotechnical measures. The method of coverage path planning of heterogenic UAVs group based on a genetic algorithm is proposed; this method provides planning of flight by a group of UAVs using a moving ground platform on which UAVs are recharged and refueled (multi heterogenic UAVs coverage path planning with moving ground platform (mhCPPmp)). This method allows calculating a fly by to solve the task of covering fields of different shapes and permits selecting the optimal subset of UAVs from the available set of devices; it also provides a 10% reduction in the cost of a flyby compared to an algorithm that does not use heterogeneous UAVs or a moving platform.
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