Francesco Misino
Development of a multi-UAS coverage planning algorithm based on the Ant Colony optimization.
Rel. Giorgio Guglieri, Stefano Primatesta. Politecnico di Torino, Master of science program in Aerospace Engineering, 2022
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Abstract
This thesis focuses on the coverage planning problem with multiple UAVs (Unmanned aerial Vehicles), also called drone. The aim is to minimize the coverage time of an operational area with the presence of several obstacles. The strategy adopted divides the operational area to be covered into several regions, and, then, assigns them to the corresponding UAV. The choice for the optimization algorithm was made through a literature search of the different methods proposed at the state of the art, focusing on those peculiar to multi-drone aerial systems. The method adopted is based on the use of Voronoi diagram and Delaunay triangulation to decompose the operational area into regions.
Thus, an algorithm based on the bio-inspired Ant Colony method provides an optimization by assigning the different regions to each UAV, as well as defining the order of visit each region, evaluating the parameters of drones, such as cruise speed and the field of view of the sensor used in the coverage application
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