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TactoFind: A Tactile Only System for Object Retrieval

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arxiv 2303.13482 v1 pith:ENBIRGGX submitted 2023-03-23 cs.RO cs.AIcs.CVcs.LG

classification cs.ROcs.AIcs.CVcs.LG
keywords objectstouchobjectfeedbackonlyscenesensorsinformation
verification ladder T0 review T1 audit T2 compute T3 formal

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We study the problem of object retrieval in scenarios where visual sensing is absent, object shapes are unknown beforehand and objects can move freely, like grabbing objects out of a drawer. Successful solutions require localizing free objects, identifying specific object instances, and then grasping the identified objects, only using touch feedback. Unlike vision, where cameras can observe the entire scene, touch sensors are local and only observe parts of the scene that are in contact with the manipulator. Moreover, information gathering via touch sensors necessitates applying forces on the touched surface which may disturb the scene itself. Reasoning with touch, therefore, requires careful exploration and integration of information over time -- a challenge we tackle. We present a system capable of using sparse tactile feedback from fingertip touch sensors on a dexterous hand to localize, identify and grasp novel objects without any visual feedback. Videos are available at https://taochenshh.github.io/projects/tactofind.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Leveraging Tactile Sensing to Render both Haptic Feedback and Virtual Reality 3D Object Reconstruction in Robotic Telemanipulation

    cs.RO 2024-12 conditional novelty 6.0 of 10

    Teleoperation of a robot arm for pick-and-place can be done without cameras by combining tactile-sensor-based 3D reconstruction in VR with haptic feedback to the operator.

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