Performance Evaluation of Cooperative Task Assignment and Path Planning Algorithms in UAV Networks

This paper aims to comprehensively perform an evaluation of cooperative task assignment and path planning algorithms for unmanned aerial vehicle (UAV) networks, designed for increased operational efficiency in a plethora of mission contexts. We carry out a systematic study of a range of the state-of-the-art algorithms, ranging from classical methods to advanced machine learning models with a view to understanding their efficacy in optimizing task assignment and flight path planning under a myriad of conditions. In our study, the critical factors considered for the performance evaluation of algorithms include mission completion time, energy efficiency, and collision probability in UAV networks. The qualitative and quantitative means of analysis are used to present the extent to which the performance and reliability of each algorithm is different. The simulation results show that the right algorithm has to be selected depending on the mission requirements, being aware of mission complexity, environment unpredictability, and computation resources.