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Self-balancing control and manipulation of a glove puppet robot on a two-wheel mobile platform

机译:两轮移动平台上的手套木偶机器人的自平衡控制和操纵

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This video shows a continuing work of the glove puppet robot presented before. The major improvement from the previous work is to mount the 9-DOF mechanism, which mimicking a glove puppet manipulation, on a two-wheel mobile platform. The platform provides agile movements of the robot but itself is an unstable system. Hence, a self-balancing controller is implemented by considering the motion as well as configuration variation of the upper body (the 9-DOF mechanism). The control law utilizes the principle of computed torque method with online identification of related parameters using various sensors including an accelerometer. The incline angle is obtained by fusing a gyroscope and a tilt sensor. Under the balancing control, the forward motion of the robot is achieved by giving a desired tilt angle profile. To minimize the footprint of electronics, the controller is implemented using an 8-bit single-chip microcontroller. Further, to enhance the interaction capability of the system, a simple gesture coding using dynamic time warping identification method with Markov model is implemented for the data glove to recognize the puppet gesture by human hand.
机译:该视频显示了先前展示的手套木偶机器人的持续工作。先前工作的主要改进是在两轮移动平台上安装了9自由度机制,该机制模仿了手套木偶的操纵。该平台提供了机器人的敏捷运动,但它本身是一个不稳定的系统。因此,通过考虑上半身的运动以及配置变化(9自由度机制)来实现自平衡控制器。控制定律利用计算转矩方法的原理,并通过各种传感器(包括加速度计)在线识别相关参数。倾斜角度是通过将陀螺仪和倾斜传感器融合而获得的。在平衡控制下,机器人的向前运动是通过提供所需的倾斜角轮廓来实现的。为了最大程度地减少电子设备的面积,该控制器使用8位单芯片微控制器实现。此外,为了增强系统的交互能力,为数据手套实现了使用动态时间规整识别方法和马尔可夫模型的简单手势编码,以用于数据手套识别人手的木偶手势。

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