Slip detection helps to prevent robotic hands from dropping grasped objects and would thus enable complex object manipulation. Here we present a method of detecting slip with a biomimetic optical tactile sensor-the TacTip-that operates by measuring the positions of internal pins embedded in its compliant skin. We investigate whether local pin movement is a strong signal of slip. Accurate and robust discrimination between static and slipping objects is obtained with a support vector machine (accuracy 99.88%). We then demonstrate performance on a task in which a slipping object must be caught. For fast reaction times, a modified TacTip is made for high-speed data collection. Performance of the slip detection method is then validated under several test conditions, including varying the speed at which slip onset occurs and using novel shaped objects. The proposed methods should apply to tactile sensors that can detect the local velocities of surface movement. The sensor and slip detection methods are also well-suited for integration onto robotic hands for deploying slip control under manipulation. Index Terms-Force and tactile sensing, biomimetics. I. INTRODUCTION W HEN grasping an object, humans are able to prevent dropping it by constantly adjusting their grip [1]. This is possible due to our highly sensitive slip detection capabilities. Slip causes local movement of the skin surface, activating the Meissner corpuscles that are densely concentrated in our fingertips [2]. These mechanoreceptors initiate a reflexive action to minimise unwanted object motion [3]. Replicating this behaviour in a robotic hand will yield a more sophisticated sense of touch and enable complex object manipulation by reducing the likelihood of an object being dropped [4]. Slip detection has been an active research area since the 1980s when Howe & Cutkosky presented a solution using an accelerometer embedded in an artificial skin to detect slip [5].
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