Decentralized Dynamic Task Allocation Algorithm Based on a Bidding Mechanism

To address the multi-UAV cooperative task planning problem, this paper proposes a decentralized dynamic task allocation method based on a bidding mechanism. In this method, each UAV autonomously decides task selection through a bidding strategy and dynamically adjusts its allocation plan during execution to adapt to complex and dynamic task environments. A mathematical model for UAV task allocation is established, considering UAV states, task rewards, and execution costs. A bidding-based task allocation algorithm is designed to maximize overall utility. This approach introduces a task reward-cost tradeoff mechanism to enhance task completion rates while reducing unnecessary resource consumption. Additionally, a task-locking strategy is proposed to ensure allocation stability and minimize efficiency losses caused by frequent task switching. Simulation experiments validate that the proposed method outperforms traditional task allocation algorithms in terms of task completion rate, computational overhead, and global utility, effectively improving the task coordination capability of multi-UAV systems in dynamic environments.