Conference Paper

A Novel Multi-robot Coordination Method Based on Reinforcement Learning.

DOI: 10.1007/978-3-540-87442-3_148 Conference: Advanced Intelligent Computing Theories and Applications. With Aspects of Theoretical and Methodological Issues, 4th International Conference on Intelligent Computing, ICIC 2008, Shanghai, China, September 15-18, 2008, Proceedings
Source: DBLP


Focusing on multi-robot coordination, role transformation and reinforcement learning method are combined in this paper. Under
centralize control framework, the distance nearest rule which means that the nearest robot ranges from obstacles is selected
to be the master robot for controlling salve robots is presented. Meanwhile, different from traditional way which reinforcement
learning is applied in online learning of multi-robot coordination, this paper proposed a novel behavior weight method based
on reinforcement learning, the robot behavior weights are optimized through interacting with environment and the coordination
policy based on maximum behavior value is presented to plan the collision avoidance behavior of robot. The learning method
proposed in this paper is applied to the application related to collaboration movement of mobile robots and demonstrated by
the simulation results presented in this paper.

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