This paper proposes a controller for stable grasping of unknown-shaped objects by two robotic fingers with tactile fingertips. The grasp is stabilised by rolling the fingertips on the contact surface and applying a desired grasping force to reach an equilibrium state. The validation is both in simulation and on a fully-actuated robot hand (the Shadow Modular Grasper) fitted with custom-built optical tactile sensors (based on the BRL TacTip). The controller requires the orientations of the contact surfaces, which are estimated by regressing a deep convolutional neural network over the tactile images. Overall, the grasp system is demonstrated to achieve stable equilibrium poses on various objects ranging in shape and softness, with the system being robust to perturbations and measurement errors. This approach also has promise to extend beyond grasping to stable in-hand object manipulation with multiple fingers.
@article{arxiv.2106.01110,
title = {A Robust Controller for Stable 3D Pinching using Tactile Sensing},
author = {Efi Psomopoulou and Nicholas Pestell and Fotios Papadopoulos and John Lloyd and Zoe Doulgeri and Nathan F. Lepora},
journal= {arXiv preprint arXiv:2106.01110},
year = {2021}
}
Comments
8 pages, 10 figures, 1 appendix. Accepted for publication in IEEE Robotics and Automation Letters and in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021). Supplemental video: https://youtu.be/rfQesw3FDA4