4.6 Article

Vision-Based Tactile Sensing and Shape Estimation Using a Fluid-Type Touchpad

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TASE.2012.2206075

Keywords

Dexterous manipulation; image processing; robot hand; shape measurement; tactile sensors

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In this paper, we propose a new method to estimate the shape and irregularity of objects by a vision-based tactile sensor, which consists of a CCD camera, LED lights, transparent acrylic plate, and a touchpad which consists of an elastic membrane filled with translucent red water. Intensities of red, green and blue bands of the traveling light in the touchpad are analyzed in this study to estimate the shape/irregularity of the object. The LED light traveling in the touchpad is scattered and absorbed by the red pigment in the fluid. The depth of the touchpad is estimated by using the intensity of the light obtained from the red-green-blue (RGB) values of the image, in consideration of the scattering and reflection effects. The reflection coefficient that depends on the shape of the membrane, was decoupled in the proposed formulation. The intensity of the traveling light is represented with the geometrical parameters of the touchpad surface. In order to reduce the approximation error caused by unmodeled factors, we compensate the error by using a function of the deformation of the membrane. The validation of the proposed method is confirmed through experimental results. Note to Practitioners-More reliable and sensitive skin of robot hands is realized by shape-sensing of objects in contact. With the shape-sensing, we can achieve a stable grip of robot hands avoiding protruding portion, and obtain reliable grip positions. With shape-deformation of flexible objects, we can avoid the grasped object (with robot fingers) by controlling the grasping force. Although various types of tactile sensors for robot hands have been developed, there have been few sensors that shape-sense of objects in contact. This paper suggests a three-dimensional shape-sensing method of object in contact. The sensor can be compact in size and structure, since we use only a single camera. Although we used many parameters, the proposed method allows the practitioners to implement the proposed method in an easy manner to their applications. We should evaluate how efficient the proposed method is for various applications. Future work includes implementation to the robot hands.

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