Autonomous Behavior-Mode Switching in a Two-Mobile Robotic System : S-Temperature Based On-line Learning

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This paper deals with an autonomous behavior-mode switching in a behavior-based learning of a mobile-robotic system, which is composed of two mobile robotic modules consisting of a crawler and one DOF arm. The task is to carry a long bar horizontally along a compound road with keeping the bar-support length constant. We propose an on-line learning method "STL (S-Temperature based on-line Learning) ". During the learning process, the robotic system can build up the state categorization in terms of two-dimensional sensory data (support length and support inclination). The robotic system can transit seamlessly between the learning behavior and the task-achieving behavior according to the internal state of the robotic system that is represented by S-temperature introduced into the STL algorithms. We show the effectiveness of STL algorithm by hardware experiment and the learning characteristics with respect to important learning parameters by computer simulation experiment.
一般社団法人日本機械学会の論文
2002-03-15