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The damping controller is popularly used in human-robot interaction to adapt the desired pose of the tool center via applied wrench (force and torque) by the human. However, the experimental identification of the suitable damping gain for the dynamical relationship between applied wrench and end-effector's velocity is an open problem. In addition, although the requirements of safe human-robot standards...
A falling avoidance of biped robots is an important research topic to use the robot in a human life environment. In this paper, we propose a machine learning approach to falling detection and avoidacne for biped robots. Support Vector Machine (SVM) is used as the machine learning algorithm and it detects the falling state of the robot based on acceleration value of torso and center of pressure value...
This paper introduce a state classification method for detecting falling of biped robot. The method uses a support vector machine (SVM) to classify the state. The input vector for the SVM are a magnitude of acceleration, a position of center of pressure (CoP) in x and z axis, and tilt angles of torso relative to x and z axis. The input vector is based on sensor data that is measured from accelerometer...
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