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Human-Manipulator Interface Using Hybrid Sensors via CMAC for Dual Robots

机译:通过CMAC使用混合传感器的双机器人人机界面

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This paper presents a novel method that allows a human operator to communicate his motion to dual robot manipulators by performing his double hand-arms movements, which would naturally carry out an object manipulation task. The proposed method uses hybrid sensors to obtain the position and orientation of the human hands. Although the position and the orientation of the human hands can be obtained from the sensors, the measurement errors increase over time due to the noise of the devices and the tracking error. A cerebellar model articulation controller (CMAC) is used to estimate the position and orientation of the human hands. Due to the limitations of the perceptive and the motor, human operator can not accomplish the high precise manipulation without any assistants. An adaptive multi-space transformation (AMT) is employed to assist the operator to improve the accuracy and reliability in determining the posture of the manipulator. With making full use of the human hand-arms motion, the operator would feel kind of immersive. Using this human-robot interface, the object manipulation task done in collaboration by dual robots could be carried out flexibly through preferring the double hand-arms motion by one operator.
机译:本文提出了一种新颖的方法,该方法允许操作员通过执行双手双臂动作来将其动作传达给双机器人操纵器,这自然会执行对象操纵任务。所提出的方法使用混合传感器来获取人手的位置和方向。尽管可以从传感器获得人手的位置和方向,但是由于设备的噪声和跟踪误差,测量误差会随着时间而增加。小脑模型关节控制器(CMAC)用于估计人手的位置和方向。由于感知和运动的限制,如果没有任何助手,操作人员将无法完成高精度的操作。采用自适应多空间变换(AMT)来帮助操作员提高确定操纵器姿势的准确性和可靠性。充分利用人的手臂动作,操作员会感到身临其境。使用这种人机界面,可以通过偏爱一个操作员的双手臂动作来灵活地执行由双机器人协作完成的对象操纵任务。

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