A Multi-agent Architecture Based Cooperation and Intelligent Decision Making Method for Multirobot Systems

Authors:
Tao Yang;Jia Ma;Zeng-Guang Hou;Gang Peng;Min Tan
Affiliations:
Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China 100080;Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China 100080;Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China 100080;Department of Control Science and Control Engineering, Huazhong University of Science and Technology, Wuhan, China 430074;Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China 100080
Venue:
Neural Information Processing
Year:
2008

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Abstract

The design of a hybrid multi-agent architecture is proposed for multirobot systems. Analysis of the architecture shows that it is suitable for multirobot systems dealing with changing environments. Meanwhile, it is capable of controlling a group of robots to accomplish multiple tasks simultaneously. Two associated issues about the architecture are cooperation between robots and intelligent decision making. Ability vector, cost function and reward function are used as criteria to describe and solve the role assignment problem in multirobot cooperation. A solution of information fusion based on RBF neural networks is applied to solve the reality problem in decision making of multirobot systems. And an experiment about robot soccer shooting is designed. The experimental results verify that the method can improve the whole decision system in accuracy.