Two-scale Algorithm to Plan Coverage Paths for Multi-UAVs

Abstract

The purpose of the coverage mission is to search this space by visiting specific points (Points of Interest (POI)) in order to scan as much area as possible. This type of mission appears for a diversity of applications, we quote, for example, aerial surveillance, radioactive waste, and pollution sources localization, data collection, etc. This paper addresses the problem of aerial coverage by deploying a fleet of Unmanned Aerial Vehicles (UAVs), Indeed, the planning algorithm proposed solves how to ensure a global sampling of an Area of Interest (AOI). First, Voronoi diagram is adapted to install a grid of measurement points (POIs), while ensuring a homogeneous sample of this area. Then, optimized paths are planned for the coverage mission passing through all the POIs. Considering the flight capabilities of UAVs, the coverage mission is modeled as a Vehicle Rooting Problem (VRP) and then resolved by taking advantage of the Simulated Annealing (SA) method. A generic solution, optimization, and reduced computation time are the key advantages resulting from simulation tests.