Multi-UAV Task Reallocation Based on Auction Consensus Algorithm

This paper studies the multi-UAV task redistribution problem based on the auction consensus algorithm, aiming to improve the combat effectiveness of UAVs in dynamic battlefield environments. The article first analyzes the background and significance of unmanned aerial vehicle (UAV) mission allocation, pointing out that a single UAV is difficult to meet the complex and changeable combat requirements, and multi-UAV collaborative operations have become an inevitable choice. Then, the article elaborately introduces the multi-UAV mission allocation model, including combat scene analysis, objective function, constraint model and mission allocation coding. In a dynamic environment, a task reallocation algorithm based on consensus auction mechanism (CBAA) is proposed for unexpected situations such as new tasks, unmanned aerial vehicle malfunctions, and changes in task locations. This algorithm combines the auction mechanism with the consensus mechanism to achieve decentralized decision-making, adapt to dynamic environments, and ensure global optimization. The experimental results show that the CBAA algorithm can generate new task sequences in real time while minimizing the trajectory cost and meeting the performance constraints of unmanned aerial vehicles (UAVs), effectively deal with unexpected situations, and maintain the overall coherence and effectiveness of the tasks.