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

doi:10.1109/ICRA48891.2023.10160503

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^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

2 Citations (Scopus)

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.

Original language	English
Title of host publication	Proceedings - ICRA 2023 : IEEE International Conference on Robotics and Automation
Number of pages	7
Publisher	IEEE
Publication date	2023
Pages	12457-12463
ISBN (Electronic)	9798350323658
DOIs	https://doi.org/10.1109/ICRA48891.2023.10160503
Publication status	Published - 2023
Externally published	Yes
Event	2023 IEEE International Conference on Robotics and Automation, ICRA 2023 - London, United Kingdom Duration: 29 May 2023 → 2 Jun 2023

Conference

Conference	2023 IEEE International Conference on Robotics and Automation, ICRA 2023
Country/Territory	United Kingdom
City	London
Period	29/05/2023 → 02/06/2023

Series	Proceedings - IEEE International Conference on Robotics and Automation
Volume	2023-May
ISSN	1050-4729

Bibliographical note

Funding Information:
This work was supported by Electronics and Telecommunications Research Institute(ETRI) grant funded by the Korean government. [23ZS1300, Research on High Performance Computing Technology to overcome limitations of AI processing]. The authors would like to extend their gratitude towards Heather Culbertson et al. for sharing their haptic texture rendering code online. The authors are also grateful towards Arsen Abdulali et al. for providing their texture segmentation framework.

Publisher Copyright:
© 2023 IEEE.

Access to Document

10.1109/ICRA48891.2023.10160503

Cite this

Awan, M. I., Ogay, T., Hassan, W., Ko, D., Kang, S., & Jeon, S. (2023). Model-Mediated Teleoperation for Remote Haptic Texture Sharing: Initial Study of Online Texture Modeling and Rendering. In Proceedings - ICRA 2023: IEEE International Conference on Robotics and Automation (pp. 12457-12463). IEEE. Proceedings - IEEE International Conference on Robotics and Automation Vol. 2023-May https://doi.org/10.1109/ICRA48891.2023.10160503

Model-Mediated Teleoperation for Remote Haptic Texture Sharing : Initial Study of Online Texture Modeling and Rendering. / Awan, Mudassir Ibrahim; Ogay, Tatyana; Hassan, Waseem; Ko, Dongbeom; Kang, Sungjoo; Jeon, Seokhee.

Proceedings - ICRA 2023: IEEE International Conference on Robotics and Automation. IEEE, 2023. p. 12457-12463 (Proceedings - IEEE International Conference on Robotics and Automation, Vol. 2023-May).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Awan, MI, Ogay, T, Hassan, W, Ko, D, Kang, S & Jeon, S 2023, Model-Mediated Teleoperation for Remote Haptic Texture Sharing: Initial Study of Online Texture Modeling and Rendering. in Proceedings - ICRA 2023: IEEE International Conference on Robotics and Automation. IEEE, Proceedings - IEEE International Conference on Robotics and Automation, vol. 2023-May, pp. 12457-12463, 2023 IEEE International Conference on Robotics and Automation, ICRA 2023, London, United Kingdom, 29/05/2023. https://doi.org/10.1109/ICRA48891.2023.10160503

Awan MI, Ogay T, Hassan W, Ko D, Kang S, Jeon S. Model-Mediated Teleoperation for Remote Haptic Texture Sharing: Initial Study of Online Texture Modeling and Rendering. In Proceedings - ICRA 2023: IEEE International Conference on Robotics and Automation. IEEE. 2023. p. 12457-12463. (Proceedings - IEEE International Conference on Robotics and Automation, Vol. 2023-May). https://doi.org/10.1109/ICRA48891.2023.10160503

Awan, Mudassir Ibrahim ; Ogay, Tatyana ; Hassan, Waseem ; Ko, Dongbeom ; Kang, Sungjoo ; Jeon, Seokhee. / Model-Mediated Teleoperation for Remote Haptic Texture Sharing : Initial Study of Online Texture Modeling and Rendering. Proceedings - ICRA 2023: IEEE International Conference on Robotics and Automation. IEEE, 2023. pp. 12457-12463 (Proceedings - IEEE International Conference on Robotics and Automation, Vol. 2023-May).

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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.",

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