Deep Vibro-Tactile Perception for Simultaneous Texture Identification, Slip Detection, and Speed Estimation.

ABSTRACT: Autonomous dexterous manipulation relies on the ability to recognize an object and detect its slippage. Dynamic tactile signals are important for object recognition and slip detection. An object can be identified based on the acquired signals generated at contact points during tactile interaction. The use of vibrotactile sensors can increase the accuracy of texture recognition and preempt the slippage of a grasped object. In this work, we present a Deep Learning (DL) based method for the simultaneous texture recognition and slip detection. The method detects non-slip and slip events, the velocity, and discriminate textures-all within 17 ms. We evaluate the method for three objects grasped using an industrial gripper with accelerometers installed on its fingertips. A comparative analysis of

SUBMITTER: Massalim Y 

PROVIDER: S-EPMC7435741 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature