Table of Contents
Advances in Artificial Intelligence
Volume 2013 (2013), Article ID 256524, 11 pages
http://dx.doi.org/10.1155/2013/256524
Research Article

A Comparative Study between Optimization and Market-Based Approaches to Multi-Robot Task Allocation

1Robotics and Autonomous Systems (RAS) Research Group, German University in Cairo, New Cairo, Egypt
2Engineering Science Department, Suez University, Suez, Egypt

Received 31 May 2013; Revised 29 August 2013; Accepted 14 September 2013

Academic Editor: Jun He

Copyright © 2013 Mohamed Badreldin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper presents a comparative study between optimization-based and market-based approaches used for solving the Multirobot task allocation (MRTA) problem that arises in the context of multirobot systems (MRS). The two proposed approaches are used to find the optimal allocation of a number of heterogeneous robots to a number of heterogeneous tasks. The two approaches were extensively tested over a number of test scenarios in order to test their capability of handling complex heavily constrained MRS applications that include extended number of tasks and robots. Finally, a comparative study is implemented between the two approaches and the results show that the optimization-based approach outperforms the market-based approach in terms of optimal allocation and computational time.