Response Threshold Model Based UAV Search Planning and Task Allocation

Abstract

This paper addresses a search planning and task allocation problem for a Unmanned Aerial Vehicle (UAV) team that performs a search and destroy mission in an environment where targets with different values move around. The UAVs are heterogeneous having different sensing and attack capabilities, and carry limited amount of munitions. The objective of the mission is to find targets and eliminate them as quickly as possible considering the values of the targets. In this context, there are two distinct issues that need to be addressed simultaneously: search planning and task allocation. The search plan generates an efficient search path for each UAV to facilitate a fast target detection. The task allocation assigns UAVs attack tasks over detected targets such that each UAV's attack capability is respected. We model these two issues in one framework and propose a distributed approach that utilizes a probabilistic decision making mechanism based on response threshold model. The proposed approach accounts for natural uncertainties in the environment, and provides flexibility, resulting in efficient exploration in the environment and effective allocation of attack tasks. The approach is evaluated in simulation experiments in comparison with other methods, of which results show that our approach outperforms the other methods.