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

机译:使用Kinect捕获并通过机器学习方法识别的手势远程控制移动机器人

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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.
机译:本文的主要目的是利用机器学习方法和Kinect及其人体感应技术来设计一个简单,方便而有效的机器人远程控制系统。在这项研究中,Kinect传感器用于捕获具有深度信息的人体骨骼,并且使用反向传播神经网络设计了一种手势训练和识别方法,以通过蓝牙远程命令移动机器人执行某些操作。实验结果表明,所设计的移动机器人远程控制系统平均可以准确识别7种手势的96%以上,并且可以有效地控制设计的命令使用的真正的电子冰球机器人。

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