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EDGE EXTRACTION USING IMAGE AND THREE-AXIS TACTILE DATA

机译:使用图像和三轴触觉数据进行边缘提取

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This paper describes a hand-arm system equipped with optical three-axis tactile sensors and a binocular vision sensor. The vision compensates for the limitations of tactile information and tactile sensing, and vice versa. The tactile sensor can obtain geometrical data as real scale, while image data requires calibration to obtain length as a metric unit. Even if stereovision is used, we cannot obtain sufficient precision. In the evaluation test, the robotic hand equipped with tactile sensors traces an object including convex and concave portions to evaluate edge trace precision. Error of distance obtained by the binocular vision is around ± 10 mm when distance between the camera and object is around 600 mm. When the hand-arm robot touches the convex portion of the object, size data obtained by the vision is modified within ± 0.5 mm accuracy. Since the robotic finger is too thick to touch the bottom of the concave, size data of the concave portion obtained by tactile sensing includes relatively large error of around 4 mm. However, the robot finger can follow the contour with ± 0.5 mm accuracy except for the bottom portion. Therefore, vision sensing is not sufficient for precise edge exploration and modification based on tactile sensing is required.
机译:本文介绍了一种配备有光学三轴触觉传感器和双目视觉传感器的手臂系统。视觉补偿了触觉信息和触觉感知的局限性,反之亦然。触觉传感器可以获取几何数据作为真实比例,而图像数据需要校准以获取长度作为度量单位。即使使用了立体视觉,我们也无法获得足够的精度。在评估测试中,配备有触觉传感器的机械手会追踪包括凸凹部分的对象,以评估边缘追踪的精度。当相机和物体之间的距离约为600毫米时,通过双目视觉获得的距离误差约为±10毫米。当手臂机器人接触到物体的凸出部分时,通过视觉获得的尺寸数据将在±0.5 mm的精度范围内进行修改。由于机械手的手指太粗而无法接触凹部的底部,因此通过触觉感测获得的凹部的尺寸数据包括大约4mm的相对较大的误差。但是,除底部以外,机械手手指可以以±0.5 mm的精度跟踪轮廓。因此,视觉感测不足以进行精确的边缘探索,并且需要基于触觉感测的修改。

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