TRAJECTORY PLANNING FOR SEARCH-AND-RESCUE UAVs USING A GREEDY ALGORITHM

Abstract

This article presents a trajectory-planning program for research-and-rescue UAVs based on the use of a local optimization greedy algorithm. Trajectories are generated over a search domain characterized by a probabilistic score map. For multiple-UAV systems, the program can assign each device to a search mission based on the probabilistic property or the geometry of the search domain. Some parameters such as the maximum travelled distance and trajectory resolusion could be input into the program. In this study, the program was tested to run for a two-UAV system over a given probabilistic score map. The input trajectory paremerters were selected based on the properties of each UAV and the requirement of a search-and-rescue mission. The program may be seamlessly integrated with UAV flight control software, enabling a direct translation of the obtained trajectories into autonomous mission execution.