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An Approach for Route Optimization in Applications of Precision Agriculture Using UAVs

机译:使用无人机精密农业应用路线优化方法

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摘要

This research paper focuses on providing an algorithm by which (Unmanned Aerial Vehicles) UAVs can be used to provide optimal routes for agricultural applications such as, fertilizers and pesticide spray, in crop fields. To utilize a minimum amount of inputs and complete the task without a revisit, one needs to employ optimized routes and optimal points of delivering the inputs required in precision agriculture (PA). First, stressed regions are identified using VegNet (Vegetative Network) software. Then, methods are applied for obtaining optimal routes and points for the spraying of inputs with an autonomous UAV for PA. This paper reports a unique and innovative technique to calculate the optimum location of spray points required for a particular stressed region. In this technique, the stressed regions are divided into many circular divisions with its center being a spray point of the stressed region. These circular divisions would ensure a more effective dispersion of the spray. Then an optimal path is found out which connects all the stressed regions and their spray points. The paper also describes the use of methods and algorithms including travelling salesman problem (TSP)-based route planning and a Voronoi diagram which allows applying precision agriculture techniques.
机译:本研究文件侧重于提供一种算法(无人驾驶飞行器)无人机可用于为农作物领域提供肥料和农药喷雾等农业应用的最佳途径。为了利用最低数量的输入并完成任务而无需重新访问,需要采用优化的路线和提供精密农业所需输入的优化点(PA)。首先,使用VEGNET(营养网络)软件来识别压力区域。然后,应用方法以获得利用自主UAV喷射输入的最佳路线和点。本文报告了一种独特而创新的技术,以计算特定应力区域所需的喷射点的最佳位置。在该技术中,应力区域被分成许多圆形分裂,其中心是应力区域的喷射点。这些循环部门将确保喷雾更有效地分散。然后发现最佳路径,其连接所有压力区域及其喷射点。本文还描述了使用方法和算法,包括旅行推销员问题(TSP)的路线规划和允许应用精密农业技术的Voronoi图。

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