Control of a Ball Catch Robot Using Machine Learning

DOI

10.2991/jrnal.k.201215.005How to use a DOI?

Keywords

Machine learning; control; experiment; evaluation

Abstract

Robots, such as industrial robots, have been used in the world of industry since the 1970s. There has been particularly rapid development in the field of robots in recent years, and there has been progress in robot research in industries such as communications and automobiles. For this reason, in the near future, robots with a diverse range of applications will be required around us. In this paper, as part of foundational research on robots and artificial intelligence, we propose a method for learning ball trajectories, using machine learning, to estimate target values for the distance in which robots move. In the proposed method, we use a linear regression model for supervised learning, and validate its effectiveness through experimentation.

Copyright

© 2020 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Shinichi Imai
PY  - 2020
DA  - 2020/12/31
TI  - Control of a Ball Catch Robot Using Machine Learning
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 236
EP  - 239
VL  - 7
IS  - 4
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.k.201215.005
DO  - 10.2991/jrnal.k.201215.005
ID  - Imai2020
ER  -