research-article

Torque Contribution to Haptic Rendering of Virtual Textures

Authors:

Sahba Aghajani Pedram,

Roberta L. Klatzky,

Peter BerkelmanAuthors Info & Claims

IEEE Transactions on Haptics, Volume 10, Issue 4

Pages 567 - 579

https://doi.org/10.1109/TOH.2017.2679000

Published: 01 October 2017 Publication History

Abstract

Despite the fact that conventional haptic interfaces and rendering algorithms commonly approximate interactions with force only, the dynamic effects of even simple tasks, e.g., writing on a paper, involve both forces and torques. To extend previous algorithms as well as to investigate the effects of torque feedback on human roughness perception, we deployed a novel haptic platform with two probes, fingertip and penhandle. Three torque conditions were examined: 1) Slope Torque, which orients the probe perpendicular to the surface, 2) No Torque, where no active torque is provided by the device, and 3) Stiff Torque, where torque feedback is provided to keep the probe upright. A conventional magnitude estimation experiment was performed. The results indicated that both the torque signals and grasp type mediate human perception of virtual textures. Slope Torque led to greater perceived roughness when the fingertip was used, and the fingertip led to higher roughness ratings than the penhandle with the Slope Torque condition. The Slope Torque algorithm appears to be advantageous for generating rougher surfaces compared to the force-based algorithms which are typically limited by the system stability and actuator saturation.

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Cited By

Huang JZhao JQiu ZYuan Z(2022)Transformer Based High-Frequency Predictive Model for Visual-Haptic Feedback of Virtual Surgery NavigationNeural Information Processing10.1007/978-3-031-30111-7_13(145-157)Online publication date: 22-Nov-2022
https://dl.acm.org/doi/10.1007/978-3-031-30111-7_13

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cover image IEEE Transactions on Haptics

IEEE Transactions on Haptics Volume 10, Issue 4

October 2017

145 pages

ISSN:1939-1412

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Copyright © 2017.

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IEEE Computer Society Press

Washington, DC, United States

Publication History

Published: 01 October 2017

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Cited By

Huang JZhao JQiu ZYuan Z(2022)Transformer Based High-Frequency Predictive Model for Visual-Haptic Feedback of Virtual Surgery NavigationNeural Information Processing10.1007/978-3-031-30111-7_13(145-157)Online publication date: 22-Nov-2022
https://dl.acm.org/doi/10.1007/978-3-031-30111-7_13

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