Demo: Learning Ball Juggling in Mixed Reality with Haptic Feedback

Learning complex skills like ball juggling is usually challenging since the balls fall fast in reality. The maturity and rapid development of extended reality (XR) technologies have created opportunities to practice in a virtual environment. The challenge, however, is to connect the virtual world with the real world coherently. We develop a holistic solution with two main components: an XR environment with virtual balls whose falling speed can be adjusted and a haptic glove to provide the sense of catching the ball. By slowing down the falling speed of the balls, the learners can learn individual skills of throwing balls, catching them, and practicing juggling.

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Publication Details

Published
2025-03-17
DOI
https://doi.org/10.1109/percomworkshops65533.2025.00123
Citations
2
Primary Topic
Motor Control and Adaptation
Type
article
Field-Weighted Citation Impact
2.86

Funders

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article

Demo: Learning Ball Juggling in Mixed Reality with Haptic Feedback

Robert Rosenkranz, Frank H. P. Fitzek, Hans Winger, Giang T. Nguyen et al.
2 citations
Motor Control and Adaptation
2.86
article

Demo: Learning Ball Juggling in Mixed Reality with Haptic Feedback

Robert Rosenkranz, Frank H. P. Fitzek, Hans Winger, Giang T. Nguyen, M. Ercan Altinsoy, Volodymyr Bondarenko
article en
2 citations

Abstract

Learning complex skills like ball juggling is usually challenging since the balls fall fast in reality. The maturity and rapid development of extended reality (XR) technologies have created opportunities to practice in a virtual environment. The challenge, however, is to connect the virtual world with the real world coherently. We develop a holistic solution with two main components: an XR environment with virtual balls whose falling speed can be adjusted and a haptic glove to provide the sense of catching the ball. By slowing down the falling speed of the balls, the learners can learn individual skills of throwing balls, catching them, and practicing juggling.

Deutsche Telekom (Germany) (DE), Technische Universität Dresden (DE)
Ministry of Education, Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 10%
Motor Control and Adaptation
2.86
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