An eight-legged tactile sensor to estimate coefficient of static friction: Improvements in design and evaluation

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Abstract

According to the laws of friction, in order to initiate a sliding motion between two objects, a tangential force larger than the maximum static friction force is required. This process is governed by a material constant called the coefficient of static friction. Therefore, it is of great utility for robots to know the coefficient of static friction between its gripper and the object being manipulated, especially when a stable and precise grip on an object is necessary. Furthermore, it is most useful if the robot can estimate the coefficient of static friction upon touching an object at the very beginning of a manipulation task, instead of having to further explore the object before it tries to move the object. Motivated by this issue, we have designed (and in this paper, further improved) a novel eight-legged tactile sensor to estimate the coefficient of static friction between a planar surface and the sensing components of the prototype sensor (which will also serve as the gripper). While the basic principle of the sensor is still unchanged, here we highlight some improvements to the sensor’s design and evaluation, including more robustly controlled frictional angles (vital for the accurate sensing) and the use of a programmable xyz-stage during evaluation. The coefficients of static friction between the sensor and nine different materials were estimated and compared to a measurement obtained via traditional methods as a reference. For all testing materials, the estimated ranges cover the corresponding reference values. Good conformance with the reference coefficients is also visually indicated from a least-square fitted line of the estimated coefficients, which has a gradient close to one and an r2 value greater than 0.9.

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Chen, W., Wen, H., Khamis, H., & Redmond, S. J. (2016). An eight-legged tactile sensor to estimate coefficient of static friction: Improvements in design and evaluation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9774, pp. 493–502). Springer Verlag. https://doi.org/10.1007/978-3-319-42321-0_46

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