Tactile-Driven Gentle Grasping for Human-Robot Collaborative Tasks
Christopher J. Ford, Haoran Li, John Lloyd, Manuel G. Catalano, Matteo Bianchi, Efi Psomopoulou, Nathan F. Lepora
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.
BibTeX
@inproceedings{icra2023_tactiledrivengen,
title = {Tactile-Driven Gentle Grasping for Human-Robot Collaborative Tasks},
author = {Christopher J. Ford and Haoran Li and John Lloyd and Manuel G. Catalano and Matteo Bianchi and Efi Psomopoulou and Nathan F. Lepora},
booktitle = {ICRA 2023},
year = {2023}
}