Multi-UAV United Task Allocation via Extended Market Mechanism Based on Flight Path Cost
Jinlong Liu, Zexu Zhang, Tianlai Xu, Chao Yan · 2024
In response to the challenge of effectively allocating united tasks for multiple unmanned aerial vehicles (UAVs) in complex environments, this paper proposes an extended market mechanism task allocation method for multi-UAV united tasks under obstacle constraints. In the task information pre-construction phase, the multi-layer task lists and bidding information are constructed. In the UAV task information extension phase, by employing UAV Dubins paths to calculate flight costs and benefits, the task list and bidding information of a UAV are extended based on the greedy principle. Subsequently, in the conflict resolution phase, UAVs receive bidding information and reconstruct bidding information to achieve the consistency of allocation result. Finally, the corresponding Dubins paths are subjected to cubic B-spline optimization based on the allocation results to generate real flight paths for UAVs. Simulation experiments demonstrate the effectiveness of the proposed method in addressing the issue of united task allocation for multi-UAV in complex environments.