Group-Based Distributed Auction Algorithms for Multi-Robot Task Assignment

机器人 计算机科学 任务(项目管理) 拍卖算法 集合(抽象数据类型) 解算器 启发式 整数(计算机科学) 贪婪算法 算法 分布式算法 数学优化 分布式计算 人工智能 工程类 拍卖理论 共同价值拍卖 数学 收入等值 统计 程序设计语言 系统工程
作者
Xiaoshan Bai,Andrés Fielbaum,Maximilian Kronmüller,Luzia Knoedler,Javier Alonso–Mora
出处
期刊:IEEE Transactions on Automation Science and Engineering [Institute of Electrical and Electronics Engineers]
卷期号:20 (2): 1292-1303 被引量:11
标识
DOI:10.1109/tase.2022.3175040
摘要

This paper studies the multi-robot task assignment problem in which a fleet of dispersed robots needs to efficiently transport a set of dynamically appearing packages from their initial locations to corresponding destinations within prescribed time-windows. Each robot can carry multiple packages simultaneously within its capacity. Given a sufficiently large robot fleet, the objective is to minimize the robots’ total travel time to transport the packages within their respective time-window constraints. The problem is shown to be NP-hard, and we design two group-based distributed auction algorithms to solve this task assignment problem. Guided by the auction algorithms, robots first distributively calculate feasible package groups that they can serve, and then communicate to find an assignment of package groups. We quantify the potential of the algorithms with respect to the number of employed robots and the capacity of the robots by considering the robots’ total travel time to transport all packages. Simulation results show that the designed algorithms are competitive compared with an exact centralized Integer Linear Program representation solved with the commercial solver Gurobi, and superior to popular greedy algorithms and a heuristic distributed task allocation method. Note to Practitioners—This work presents two group-based distributed auction algorithms for a sufficiently large fleet of robots to efficiently transport a set of dynamically appearing dispersed packages from their initial locations to corresponding destinations within prescribed time-windows. Each robot can carry multiple packages simultaneously within its capacity, and the objective is to minimize the robots’ total travel time to transport all the packages within the prescribed time-windows. The paper’s practical contributions are threefold: First, the multi-robot task assignment problem is formulated through a robot-group assignment strategy, which enables complex logistic scheduling for tasks grouped according to their distributions and time-windows. Second, we theoretically show that the multi-robot task assignment problem is an NP-hard problem, which implies the necessity for designing approximate task assignment algorithms. Third, the proposed group-based distributed auction algorithms are efficient and can be adapted for real scenarios.
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