Eliminating drift of the head gesture reference to enhance Google Glass-based control of an NAO humanoid robot

• Main Authors: Xiaoqian Mao, Xi Wen, Yu Song, Wei Li, Genshe Chen
• Format: Article
• Language: English
• Published: SAGE Publishing 2017-03-01
• Series: International Journal of Advanced Robotic Systems
• Online Access: https://doi.org/10.1177/1729881417692583

This article presents a strategy for hand-free control of an NAO humanoid robot via head gesture detected by Google Glass-based multi-sensor fusion. First, we introduce a Google Glass-based robot system by integrating the Google Glass and the NAO humanoid robot, which is able to send robot commands through Wi-Fi communications between the Google Glass and the robot. Second, we detect the operator’s head gestures by processing data from multiple sensors including accelerometers, geomagnetic sensors and gyroscopes. Next, we use a complementary filter to eliminate drift of the head gesture reference, which greatly improves the control performance. This is accomplished by the high-pass filter component on the control signal. Finally, we conduct obstacle avoidance experiments while navigating the robot to validate the effectiveness and reliability of this system. The experimental results show that the robot is smoothly navigated from its initial position to its destination with obstacle avoidance via the Google Glass. This hands-free control system can benefit those with paralysed limbs.