Multi-fingered Tactile Servoing for Grasping Adjustment under Partial Observation
Hanzhong Liu, Bidan Huang, Qiang Li, Yu Zheng, Yonggen Ling, Wangwei Lee, Yi Liu, Ya-Yen Tsai
Abstract
Grasping of objects using multi-fingered robotic hands often fails due to small uncertainties in the hand motion control and the object's pose estimation. To tackle this problem, we propose a grasping adjustment strategy based on tactile seroving. Our technique employs feedback from a sensorized multi-fingered robotic hand to collaboratively servo the fingers and palm to achieve the desired grasp. We demonstrate the performance of our method through simulation and physical experiments by having a robot grasp different objects under conditions of variable uncertainty. The results show that our approach achieved a higher success rate and tolerated greater uncertainty than an open-looped grasp.
BibTeX
@inproceedings{iros2022_multifingeredtac,
title = {Multi-fingered Tactile Servoing for Grasping Adjustment under Partial Observation},
author = {Hanzhong Liu and Bidan Huang and Qiang Li and Yu Zheng and Yonggen Ling and Wangwei Lee and Yi Liu and Ya-Yen Tsai and Chenguang Yang},
booktitle = {IROS 2022},
year = {2022}
}