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

机译:消除了头部手势参考的漂移,从而增强了基于Google Glass的NAO人形机器人的控制

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摘要

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.
机译:本文提出了一种策略,该策略可通过基于Google Glass的多传感器融合检测到的头部手势来对NAO人形机器人进行免提控制。首先,我们通过集成Google Glass和NAO人形机器人引入基于Google Glass的机器人系统,该系统能够通过Google Glass和机器人之间的Wi-Fi通信发送机器人命令。其次,我们通过处理来自多个传感器(包括加速度计,地磁传感器和陀螺仪)的数据来检测操作员的头部手势。接下来,我们使用一个互补滤波器来消除头部手势参考的漂移,从而大大提高了控制性能。这是通过控制信号上的高通滤波器组件实现的。最后,我们在导航机器人的同时进行了避障实验,以验证该系统的有效性和可靠性。实验结果表明,该机器人可以通过Google Glass避开障碍物,从初始位置平稳地导航到目的地。这种免提控制系统可使四肢瘫痪的患者受益。

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