NDLI: Evolutionary Computation Approach to Decentralized Multi-robot Task Allocation

Content Provider	IEEE Xplore Digital Library
Author	Ping-an Gao Zi-xing Cai Ling-li Yu
Copyright Year	2009
Abstract	The problem of allocating exploration tasks to a team of mobile robots was addressed in this paper. Each task consists of a site location that needs to be explored by a robot. The objective of the allocation is to minimize the maximum path cost of the robots. Auction-based methods are efficient for decentralized mobile robots to allocate tasks. However, the quality of allocation cannot be guaranteed. This paper presents a decentralized allocation algorithm which combines a sequential single-task auction and task transfer among the robots. After all of the tasks are auctioned off, the robots of the same sub-team transfer tasks to improve the quality of allocation. In order to increase the efficiency of task transferring, the tasks allocated to the sub-team are clustered using an orthogonal genetic algorithm. Each robot determines which tasks should be transferred, and to which robots the tasks should be transferred according to the clusters. The validity of the proposed algorithm was verified with some benchmarks of vehicle routing problem and traveling salesperson problem. The results showed that the proposed algorithm decreased the robot path costs 40% more than that of a well-known auction-based algorithm in most cases.
Starting Page	415
Ending Page	419
File Size	907857
Page Count	5
File Format	PDF
ISBN	9780769537368
DOI	10.1109/ICNC.2009.123
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	task cluster Costs Communication system control Evolutionary computation Mobile robots Centralized control Genetic algorithms Vehicles Information science Robot kinematics single-task auction orthogonal genetic algorithm Clustering algorithms multi-robot task allocation
Content Type	Text
Resource Type	Article

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