Simulation study demonstrates superior task allocation in unmanned aerial vehicles, suggesting improved swarm coordination with minimal communication overhead.
In this paper, a novel algorithm has been developed for optimal task allocation of Unmanned Aerial Vehicles (UAVs). The centralized and distributed algorithms in the literature are studied in detail. Furthermore, market-based and threshold-based approaches have been proposed for the task assignment of UAVs by combining these algorithms with the nature of the problem. Their effects on task assignment problems in autonomous vehicles (AUVs) are compared. Hence, aggregating the advantages of both algorithms aims to reach the optimal value with a minimum number of communications. Therefore, two different algorithms were combined synergically. In addition, a 6-DOF quadrotor was modelled in MATLAB/SIMULINK to test the algorithms. Single and multi-task assignments have been tested for different scenarios in dynamic environments. According to the simulation results, the proposed algorithm's performance was proven to be superior to other algorithms.
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Ozturk et al. (2024) studied this question.
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