Intuitive Humanoid Robot Operating System Based on Recognition and Variation of Human Body Motion
In this paper, we propose an intuitive operating system for humanoid robot based on recognition and variation of human body motion. In this system, human body motion is dynamically sensed by six-axis sensors in controllers held in user’s hands. Then, the variation of human body motion is also recognized by gyro sensors in the controllers. Based on the obtained sensor information, the body motion classifier is constructed using Hidden Markov Model. By using the body motion classifier, the proposed system recognizes user’s body motion, and redundant motions of humanoid robot are prevented. User can intuitively operate humanoid robot and make it do the user’s intending motion. We conduct a task experiment to evaluate the usability of proposed system. In the experiment, for comparison with the proposed system, we prepare three methods of operation: joystick, kinect, and operating system using six-axis sensor without recognizing the variation of human body motion. As the result, comparing with other systems, we confirmed that the proposed system has more versatility and the humanoid robot could be more appropriately operated with the proposed system. And it was suggested that the proposed system enables user to operate humanoid robot, appropriately and intuitively.
KeywordsHide Markov Model Humanoid Robot Robot Control High Recognition Rate Recognition Section
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