机器人联盟任务分配的分布式拍卖算法

IF 9.4 1区 计算机科学 Q1 ROBOTICS
Ruiliang Deng;Rui Yan;Peinan Huang;Zongying Shi;Yisheng Zhong
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引用次数: 0

摘要

本研究探讨了机器人联盟的任务分配问题,这是在实际场景中遇到的问题,如多人避险游戏。与单个机器人执行每个任务的经典任务分配问题不同,这里考虑的问题涉及需要由两个机器人组成的机器人联盟执行的任务。这个任务分配问题是 3 集打包问题的一个特殊实例,众所周知,3 集打包问题是非确定性多项式时间(NP)困难问题。我们引入了 $\epsilon$-coalition-competitive equilibrium($\epsilon$-CCE)的概念,以描述一种能提供性能保证的近似解。为了在有限的迭代次数内找到$\epsilon$-CCE,我们开发了一种分布式拍卖算法。此外,还对拍卖算法进行了若干改进,以适应任务分配问题可能随时间变化的实际应用。数值模拟证明,分布式算法达到了令人满意的近似质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Distributed Auction Algorithm for Task Assignment With Robot Coalitions
This study addresses the task assignment problem with robot coalitions, as encountered in practical scenarios, such as multiplayer reach-avoid games. Unlike the classical assignment problem where a single robot performs each task, the problem considered here involves tasks that require execution by a robot coalition consisting of two robots. This task assignment problem is a special instance of 3-set packing problem, which is known to be nondeterministic polynomial time (NP)-hard. We introduce the concept of $\epsilon$ -coalition-competitive equilibrium ( $\epsilon$ -CCE) to characterize a kind of approximate solution that offers guaranteed performance. A distributed auction algorithm is developed to find an $\epsilon$ -CCE within a finite number of iterations. In addition, several enhancements have been implemented to adapt the auction algorithm for practical applications where the task assignment problem may vary over time. Numerical simulations demonstrate that the distributed algorithm achieves satisfactory approximation quality.
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来源期刊
IEEE Transactions on Robotics
IEEE Transactions on Robotics 工程技术-机器人学
CiteScore
14.90
自引率
5.10%
发文量
259
审稿时长
6.0 months
期刊介绍: The IEEE Transactions on Robotics (T-RO) is dedicated to publishing fundamental papers covering all facets of robotics, drawing on interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, and beyond. From industrial applications to service and personal assistants, surgical operations to space, underwater, and remote exploration, robots and intelligent machines play pivotal roles across various domains, including entertainment, safety, search and rescue, military applications, agriculture, and intelligent vehicles. Special emphasis is placed on intelligent machines and systems designed for unstructured environments, where a significant portion of the environment remains unknown and beyond direct sensing or control.
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