Remotely controlling of mobile robots using gesture captured by the Kinect and recognized by machine learning method

Roy CHaoming Hsu; Jhih-Wei Jian; Chih-Chuan Lin; Chien-Hung Lai; Cheng-Ting Liu

doi:10.1117/12.2008456

4 February 2013 Remotely controlling of mobile robots using gesture captured by the Kinect and recognized by machine learning method

Roy CHaoming Hsu, Jhih-Wei Jian, Chih-Chuan Lin, Chien-Hung Lai, Cheng-Ting Liu

Author Affiliations +

Proceedings Volume 8662, Intelligent Robots and Computer Vision XXX: Algorithms and Techniques; 86620B (2013) https://doi.org/10.1117/12.2008456
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

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.

Citation Download Citation

Roy CHaoming Hsu, Jhih-Wei Jian, Chih-Chuan Lin, Chien-Hung Lai, and Cheng-Ting Liu "Remotely controlling of mobile robots using gesture captured by the Kinect and recognized by machine learning method", Proc. SPIE 8662, Intelligent Robots and Computer Vision XXX: Algorithms and Techniques, 86620B (4 February 2013); https://doi.org/10.1117/12.2008456

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