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The Scientific World Journal
Volume 2014 (2014), Article ID 818701, 12 pages
Research Article

Modeling of Task Planning for Multirobot System Using Reputation Mechanism

1School of Computer and Communication Engineering, University of Science and Technology, Beijing 100083, China
2Department of Aerospace Engineering, Ryerson University, 350 Victoria Street, Toronto, ON, Canada M5B 2K3
3School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China
4ANU College of Engineering and Computer Science, Australian National University, Canberra, ACT 2601, Australia

Received 15 August 2013; Accepted 14 November 2013; Published 4 February 2014

Academic Editors: C.-C. Chang, Y. Lu, J. Shu, and F. Yu

Copyright © 2014 Zhiguo Shi 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.


Modeling of task planning for multirobot system is developed from two parts: task decomposition and task allocation. In the part of task decomposition, the conditions and processes of decomposition are elaborated. In the part of task allocation, the collaboration strategy, the framework of reputation mechanism, and three types of reputations are defined in detail, which include robot individual reputation, robot group reputation, and robot direct reputation. A time calibration function and a group calibration function are designed to improve the effectiveness of the proposed method and proved that they have the characteristics of time attenuation, historical experience related, and newly joined robot reward. Tasks attempt to be assigned to the robot with higher overall reputation, which can help to increase the success rate of the mandate implementation, thereby reducing the time of task recovery and redistribution. Player/Stage is used as the simulation platform, and three biped-robots are established as the experimental apparatus. The experimental results of task planning are compared with the other allocation methods. Simulation and experiment results illustrate the effectiveness of the proposed method for multi-robot collaboration system.