Journal of Robotics, Networking and Artificial Life

Volume 7, Issue 1, June 2020, Pages 27 - 29

Intention Classification of a User of a Walking Assist Cart by using Support Vector Machine

Authors
Noritaka Sato*, Tomoki Yokotani, Yoshifumi Morita
Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Gokiso-cho, Syowa-ku, Nagoya, Aichi 466-8555, Japan
*Corresponding author. Email: sato.noritaka@nitech.ac.jp
Corresponding Author
Noritaka Sato
Received 10 November 2019, Accepted 20 February 2020, Available Online 14 May 2020.
DOI
10.2991/jrnal.k.200512.006How to use a DOI?
Keywords
Walking assist cart; support vector machine; intention classification; artificial intelligence
Abstract

To develop better assist function for a walking assist cart, we focused on the prediction of the intention of a user. As the first step of the research, the forces and torques to the cart from the user’s hands, and the rotational velocities of the wheels are sensing. And the support vector machine is used for intention classification. As a result, we confirmed that our method was able to predict the intention of the user with enough accuracy.

Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
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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Journal
Journal of Robotics, Networking and Artificial Life
Volume-Issue
7 - 1
Pages
27 - 29
Publication Date
2020/05/14
ISSN (Online)
2352-6386
ISSN (Print)
2405-9021
DOI
10.2991/jrnal.k.200512.006How to use a DOI?
Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
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/).

Cite this article

TY  - JOUR
AU  - Noritaka Sato
AU  - Tomoki Yokotani
AU  - Yoshifumi Morita
PY  - 2020
DA  - 2020/05/14
TI  - Intention Classification of a User of a Walking Assist Cart by using Support Vector Machine
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 27
EP  - 29
VL  - 7
IS  - 1
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.k.200512.006
DO  - 10.2991/jrnal.k.200512.006
ID  - Sato2020
ER  -