An Asynchronous Multi-Task Iterative Auction-Based Method for Distributed Multi-UAV Task Scheduling
Hongsong Li, Yexun Xi, Zhen Xiong, Jie Li · 2025
This paper addresses the multi-objective and multi-task cooperative planning problem for multi-UAV swarms in dy namic complex environments by proposing a distributed task scheduling method based on Asynchronous Multi-Task Iterative Auction (AMTIA). By constructing a multi-level task dependency model combined with temporal constraints and state mechan isms to ensure task logical integrity, designing a hybrid bidding strategy integrating complementary slackness conditions and t he highest-bid-first principle to resolve auction non-convergence issues in asynchronous environments, and proposing a hybrid communication strategy combining timestamp integration with primary-secondary round protocol to reduce communication o verhead while ensuring task consistency under asynchronous conditions, a virtual-reality integrated ad-hoc network simulation platform is established to validate the algorithm's effectiveness in$2 \mathrm{v} 1,3 \mathrm{v} 2$, and 32 v 7 scenarios through Monte Carlo experime nts. The results demonstrate that the dynamic price updating mechanism reduces invalid bidding attempts, while the timestamp and primary-secondary conflict resolution rules decrease redundant message retransmissions.