Cover missions planning for unmanned aerial vehicles

Abstract

Unmanned Aerial Vehicles are starting to be used for photogrammetric sensing, in several applications, such as precision agriculture, topography and search and rescue. This, thanks to the advantages they offer over platforms like satellites and manned airplanes, such as: greater spatial and temporal resolution and also low operating costs. However, they have a limiting flight time making necessary to obtain paths that optimize the resources. In this article, we present the study of three heuristic algorithms for coverage path planning, Wavefront, Spanning-tree based coverage and a new algorithm based on expansion by weight functions, called Sunshine with the aim of finding the best strategy to find coverage routes and their subsequent use in Precision Agriculture (PA). These methods are validated by means of simulation at different wind speeds in order to analyze how the energy consumption and the total path traveled differ according to this.