A Local Optimization Technique for Assigning New Targets to the Planned Routes of Unmanned Aerial Vehicles

Abstract

— Using Unmanned Aerial Vehicles (UAVs) for reconnaissance purposes requires dynamic route planning. For example, when some of the UAVs are lost or new targets pops up during the mission, routes of each UAV should be re-arranged accordingly. This article proposes an iterative local optimization for the distribution of new targets to the existing routes in such circumstances. The proposed iterative insertion algorithm basically executes in phases. In the first phase of the algorithm, a selected UAV’s route is updated by trying to insert new targets if possible. In the second phase, a 2-opt technique is applied to the modified UAV routes for minimizing the route distance. After the second phase, if there remains some uncovered targets we begin to run the first phase again. The proposed algorithm will terminate either all the new targets are covered or 2-opt technique does not produce any better route distances. The simulation results of the iterative insertion algorithm show the effectiveness and the success of the proposed algorithm