Adaptive Task Allocation for Multi-UAV Systems Using a Novel Dynamic Distributed Algorithm

This paper introduces the Dynamic Efficient Distributed Performance Impact (DEDPI) algorithm for optimizing task allocation in multi-UAV systems operating in dynamic environments. The algorithm overcomes the limitations of existing approaches, specifically the suboptimal solutions of dynamic task algorithms and the computational inefficiencies of extending static algorithms to dynamic contexts, by dynamically adjusting task queues and employing a novel objective function to enhance resource allocation and responsiveness. Experimental results demonstrate that DEDPI significantly increases the number of completed tasks while reducing the average task execution cost, providing an effective solution for real-time, mission-critical UAV operations.