一种分布式异构多AUV任务分配鲁棒拍卖算法

为了解决异构多自主式水下航行器(AUV)的任务分配问题，提出了一种分布式鲁棒拍卖算法。建立了异构多AUV任务分配分布式拍卖模型，包括任务分配系统(拍卖商)的优化模型及AUV的优化模型。针对现有拍卖算法忽略拍卖商的利益，不符合市场规律的问题，引入任务奖励反馈机制，任务分配系统通过多轮试探拍卖市场，自适应地调整任务奖励，达到保证AUV效用的同时，有效降低任务分配系统成本的目的，促进了任务分配系统参与拍卖。针对水下洋流对任务分配模型产生的不确定性因素，提出了一种鲁棒优化算法对抗不确定性因素，提高了多AUV任务分配系统应对复杂水下环境的能力。仿真结果证明了所提算法的鲁棒性和有效性。 

A robust auction algorithm for distributed heterogeneous multi-AUV task assignment

In order to solve the task assignment problem of multiple heterogeneous autonomous underwater vehicle (AUV), a distributed robust auction algorithm is proposed. First, a heterogeneous multi-AUV task assignment distributed auction model is established, including the task assignment system (auctioneer) optimization model and the AUV optimization model. Second, in view of the existing auction algorithms that ignore the interests of the auctioneer and do not conform to the market rules, we introduce task reward feedback mechanism, and the task assignment system, through several rounds of testing the auction market, adaptively adjusts the task rewards, which effectively reduces the cost of task assignment system when guaranteeing AUV utility at the same time, for the purpose of promoting the task assignment system to participate in the auction. Finally, a robust optimization algorithm is proposed to deal with the uncertainties caused by underwater ocean currents, which improves the ability of multi-AUV task assignment system to deal with complex underwater environment. Simulation results show the robustness and effectiveness of the proposed algorithm.