Optimal Haptic Feedback in VR/AR Interfaces

Project Details

Description

Haptic feedback is a critical feature in VR/AR systems affecting user performance and experience. Previously haptic feedback has been designed via trial and error or in psychophysics experiments. However, this approach faces three issues: (1) it does not adapt to the individual user; (2) psychophysics studies use discrete levels that miss many finer opportunities for improvement; (3) they normally address only a low number of design parameters. The goal of this collaboration is to develop computational approaches to the adaptation of haptic feedback that can significantly improve the usability, expressiveness, and experience of AR/VR technology for individuals. We will study computational methods, especially generative user models and optimization, that can (1) tune the parameters of a haptic system to an individual user, (2) use continuous optimization schemes that exploit the full range of the haptic parameters, and (3) can address a larger number of objectives in a single system.
StatusFinished
Effective start/end date27/01/202031/08/2022

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  • Investigating Positive and Negative Qualities of Human-in-the-Loop Optimization for Designing Interaction Techniques

    Chan, L., Liao, Y. C., Mo, G. B., Dudley, J. J., Cheng, C. L., Kristensson, P. O. & Oulasvirta, A., 28 Apr 2022, CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. ACM, 14 p. 112. (Conference on Human Factors in Computing Systems - Proceedings).

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Open Access
    20 Citations (Scopus)