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Proceedings Paper

Remotely controlling of mobile robots using gesture captured by the Kinect and recognized by machine learning method
Author(s): Roy CHaoming Hsu; Jhih-Wei Jian; Chih-Chuan Lin; Chien-Hung Lai; Cheng-Ting Liu
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Paper Abstract

The main purpose of this paper is to use machine learning method and Kinect and its body sensation technology to design a simple, convenient, yet effective robot remote control system. In this study, a Kinect sensor is used to capture the human body skeleton with depth information, and a gesture training and identification method is designed using the back propagation neural network to remotely command a mobile robot for certain actions via the Bluetooth. The experimental results show that the designed mobile robots remote control system can achieve, on an average, more than 96% of accurate identification of 7 types of gestures and can effectively control a real e-puck robot for the designed commands.

Paper Details

Date Published: 4 February 2013
PDF: 9 pages
Proc. SPIE 8662, Intelligent Robots and Computer Vision XXX: Algorithms and Techniques, 86620B (4 February 2013); doi: 10.1117/12.2008456
Show Author Affiliations
Roy CHaoming Hsu, National Chiayi Univ. (Taiwan)
Jhih-Wei Jian, National Chiayi Univ. (Taiwan)
Chih-Chuan Lin, National Chiayi Univ. (Taiwan)
Chien-Hung Lai, National Chiayi Univ. (Taiwan)
Cheng-Ting Liu, National Chiayi Univ. (Taiwan)


Published in SPIE Proceedings Vol. 8662:
Intelligent Robots and Computer Vision XXX: Algorithms and Techniques
Juha Röning; David Casasent, Editor(s)

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