[2303.09346] Tactile-Driven Gentle Grasping for Human-Robot Collaborative Tasks
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Computer Science > Robotics

arXiv:2303.09346 (cs)
[Submitted on 16 Mar 2023]

Title:Tactile-Driven Gentle Grasping for Human-Robot Collaborative Tasks

Authors:Christopher J. Ford, Haoran Li, John Lloyd, Manuel G. Catalano, Matteo Bianchi, Efi Psomopoulou, Nathan F. Lepora
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Abstract:This paper presents a control scheme for force sensitive, gentle grasping with a Pisa/IIT anthropomorphic SoftHand equipped with a miniaturised version of the TacTip optical tactile sensor on all five fingertips. The tactile sensors provide high-resolution information about a grasp and how the fingers interact with held objects. We first describe a series of hardware developments for performing asynchronous sensor data acquisition and processing, resulting in a fast control loop sufficient for real-time grasp control. We then develop a novel grasp controller that uses tactile feedback from all five fingertip sensors simultaneously to gently and stably grasp 43 objects of varying geometry and stiffness, which is then applied to a human-to-robot handover task. These developments open the door to more advanced manipulation with underactuated hands via fast reflexive control using high-resolution tactile sensing.
Comments: Manuscript accepted to ICRA 2023. 6+n pages, 7 figures
Subjects: Robotics (cs.RO)
Cite as: arXiv:2303.09346 [cs.RO]
  (or arXiv:2303.09346v1 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2303.09346

Submission history

From: Christopher Ford [view email]
[v1] Thu, 16 Mar 2023 14:26:48 UTC (25,290 KB)
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