The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Online ISSN : 2424-3124
2017
Session ID : 2P1-F05
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Improvement of learning speed of robot behavior for object recognition
Takuya SUGIMOTOManabu GOUKO
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Abstract

We have proposed active perception system which can learn an exploratory behavior using reinforcement learning.This system acquires an effective behavior which extracts features from objects.However,the learning method of the system requires the long time to complete learning. In this study,we improve previous method.We propose new learning method that can learn more efficient than the previous one.We apply our new method to a mobile robot simulation to observe its effectiveness.Results indicate that the new method accelerates the learning.

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© 2017 The Japan Society of Mechanical Engineers
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