Distributed Decision-Making in Modular Drone Swarms

Recent advancements in modular drone swarms have introduced new challenges, particularly in the allocation of tasks within time-constrained scenarios and complex environments. This study proposes an adaptation of the Harmony DTA (Drone task allocation) algorithm, originally designed for multi-agent systems, to address the specific requirements of modular drone swarms. The Harmony DTA algorithm is enhanced with a decision-making module that allows drones to autonomously split based on the urgency of tasks and the drones workload. Simulation results prove that this approach enhances the efficiency of task assignment, decreases the total flight distance and increases the performance of time critical tasks. This study emphasizes the significance of distributed decision-making algorithms for modular drone swarms and aims to serve as a valuable reference for future research in this rapidly evolving field.