The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Online ISSN : 2424-3124
2020
Session ID : 2A1-A11
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Reflection Motion Learning of Real Robot using Deep Neural Network
Joint Research and Development of Hitachi, Ltd. and Waseda University
*Hiroshi ITOKenjiro YAMAMOTOHiroki MORITetsuya OGATA
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Abstract

A motion generation method using deep learning has been proposed that is robust against various environmental changes. In this paper, we describe a reflection motion method that responds immediately to environmental changes. The reflection motion can be developed using a simple feed-forward neural network. The tasks of verifying the reflex movement were ”grip force control” that grips various objects without crushing them, and ”obstacle avoidance” that avoids unknown objects during autonomous movement. Results of an experiment using a real robot confirmed a reflection motion could be generated.

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© 2020 The Japan Society of Mechanical Engineers
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