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A Tactile Recognition System Mimicking Human Mechanism for Recognizing Surface Roughness

机译:模仿人为识别表面粗糙度的机制的触觉识别系统

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A mathematical model was formulated on the basis of results from psychophysical experiments in which human subjects discriminated fine steps on aluminum plates. The mathematical model emulated the real neuron discharge caused when a membrane potential exceeds a threshold. This membrane potential was determined by spatial and temporal summations of postsynaptic potential. To evaluate the mathematical model for surface texture recognition by robots, we performed a series of surface-detection experiments using a robotic manipulator equipped with an optical three-axis tactile sensor. The single sensor cell of this sensor consisted of a columnar feeler and a 2-by-2 array of conical feelers. The three-axis force was calculated from the area-sum and area-difference of the conical feelers' contact areas. The robotic manipulator rubbed the tactile sensor on four brass plates with step heights of 0, 0.05, 0.1 and 0.2 mm. Results showed that the mathematical model could distinguish these step heights in real time.
机译:根据心理物理实验的结果制定了数学模型,在该实验中,人类受试者区分了铝板上的精细台阶。该数学模型模拟了当膜电位超过阈值时引起的实际神经元放电。该膜电位由突触后电位的时空总和确定。为了评估用于机器人识别表面纹理的数学模型,我们使用配备了光学三轴触觉传感器的机器人操纵器进行了一系列表面检测实验。该传感器的单个传感器单元由一个圆柱状触头和一个2×2的锥形触头阵列组成。根据圆锥形触头接触面积的面积总和和面积差计算三轴力。机器人操纵器在四个黄铜板上摩擦了触觉传感器,台阶高度分别为0、0.05、0.1和0.2 mm。结果表明,该数学模型可以实时区分这些台阶高度。

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