Model-Mediated Teleoperation for Remote Haptic Texture Sharing: Initial Study of Online Texture Modeling and Rendering
Mudassir Ibrahim Awan, Tatyana Ogay, Waseem Hassan, Dongbeom Ko, Sungjoo Kang, Seokhee Jeon
Abstract
While model-mediated teleoperation (MMT) is an effective alternative for ensuring both transparency and stability, its potential in transmitting surface haptic texture is not yet explored. This paper introduces the first MMT framework capable of sharing surface haptic texture. The follower side collects physical signals contributing to haptic texture perception, e.g., high frequency acceleration, and streams them to the leader side. The leader side uses the signals to build and update a local measurement-based texture simulation model that reflects the remote surface. At the same time, the leader runs local simulation using the model, resulting in non-delayed, stable, and accurate feedback of texture. Considering that rendering haptic texture needs tougher real-time requirements, e.g., higher update rate and lower action-feedback latency, MMT can be a perfect platform for remote texture sharing. An initial proof-of-concept system supporting single and homogeneous surface is implemented and evaluated, demonstrating the potential of the approach.
BibTeX
@inproceedings{icra2023_modelmediatedtel,
title = {Model-Mediated Teleoperation for Remote Haptic Texture Sharing: Initial Study of Online Texture Modeling and Rendering},
author = {Mudassir Ibrahim Awan and Tatyana Ogay and Waseem Hassan and Dongbeom Ko and Sungjoo Kang and Seokhee Jeon},
booktitle = {ICRA 2023},
year = {2023}
}