Online Transfer and Adaptation of Tactile Skill: A Teleoperation Framework
Abstract
This paper presents a teleoperation framework designed for online learning and adaptation of tactile skills, which provides an intuitive interface without need for physical access to execution robot. The proposed tele-teaching approach utilizes periodical Dynamical Movement Primitives (DMP) and Recursive Least Square (RLS) for generating tactile skills. An autonomy allocation strategy, guided by the learning confidence and operator intention, ensures a smooth transition between human demonstration to autonomous robot operation. Our experimental results with two 7 Degree of Freedom (DoF) Franka Panda robot demonstrates that the tele-teaching framework facilitates online motion and force learning and adaptation within a few iterations.
Cite
Text
Chen et al. "Online Transfer and Adaptation of Tactile Skill: A Teleoperation Framework." Proceedings of The 8th Conference on Robot Learning, 2024.Markdown
[Chen et al. "Online Transfer and Adaptation of Tactile Skill: A Teleoperation Framework." Proceedings of The 8th Conference on Robot Learning, 2024.](https://mlanthology.org/corl/2024/chen2024corl-online/)BibTeX
@inproceedings{chen2024corl-online,
title = {{Online Transfer and Adaptation of Tactile Skill: A Teleoperation Framework}},
author = {Chen, Xiao and Ni, Tianle and Karacan, Kübra and Sadeghian, Hamid and Haddadin, Sami},
booktitle = {Proceedings of The 8th Conference on Robot Learning},
year = {2024},
pages = {4981-4995},
volume = {270},
url = {https://mlanthology.org/corl/2024/chen2024corl-online/}
}