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abstract

Actuated Club: Modification of Golf-Club Posture with force feedback and motion prediction in VR environment

Published: 17 August 2020 Publication History

Abstract

In the golf, the trajectory and posture of the golf club during the swing influence on the direction and trajectory of the hit ball. While the instructor and the system instruct how to improve the swing, it is difficult to correct the swing motion during the swing due to lack of information quantity, time for interpretation of presented information, and lack of the sense of agency in the swing motion. Therefore, in this study, we realize the modification of the swing motion during the swing using the trajectory prediction of the golf swing and the non-grounding type force display. To cope the delay between the command of the modification and the swing correction, this system learns the golf swing trajectory of the user in advance, and predicts them. If the result of the prediction suggests the club deviates from the ideal trajectory or posture, the gyroscope presents torque in the ideal trajectory direction to correct the trajectory or posture. By practicing VR golf using the proposed system, the user can always practice golf-swing with the ideal trajectory, and can make the swing practice efficient.

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References

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Atsuki Ikeda, Dong-Hyun Hwang, Hideki Koike, G Bruder, S Yoshimoto, and S Cobb. 2018. AR based Self-sports Learning System using Decayed Dynamic TimeWarping Algorithm. In ICAT-EGVE. 171–174.
[2]
Theodore P Jorgensen and Theodore J Jorgensen. 1999. The physics of golf. Springer Science & Business Media.
[3]
RoboGolfPro. 2017. Robogolf Pro. https://robogolfpro.com/
[4]
Yuka Tanaka, Homare Kon, and Hideki Koike. 2018. A Real-Time Golf-Swing Training System Using Sonification and Sound Image Localization. In Proceedings of the 24th ACM Symposium on Virtual Reality Software and Technology (Tokyo, Japan) (VRST ’18). Association for Computing Machinery, New York, NY, USA, Article 66, 2 pages. https://doi.org/10.1145/3281505.3281604
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Kyle N. Winfree, Jamie Gewirtz, Thomas Mather, Jonathan Fiene, and Katherine J. Kuchenbecker. 2009. A high fidelity ungrounded torque feedback device: The iTorqU 2.0. In World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. 261–266. https://doi.org/10.1109/WHC.2009.4810866
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Erwin Wu and Hideki Koike. 2019. FuturePose - Mixed Reality Martial Arts Training Using Real-Time 3D Human Pose Forecasting With a RGB Camera. In 2019 IEEE Winter Conference on Applications of Computer Vision (WACV). 1384–1392.
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Hiroaki Yano, Masayuki Yoshie, and Hiroo Iwata. 2003. Development of a non-grounded haptic interface using the gyro effect. In 11th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 2003. HAPTICS 2003. Proceedings.32–39. https://doi.org/10.1109/HAPTIC.2003.1191223
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Cited By

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  • (2023)AI Coach: A Motor Skill Training System using Motion Discrepancy DetectionProceedings of the Augmented Humans International Conference 202310.1145/3582700.3582710(179-189)Online publication date: 12-Mar-2023
  • (2023)Gino .Aiki: Mixed Reality-based Physical Motor Skill Training in Aikido2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)10.1109/ISMAR-Adjunct60411.2023.00112(519-524)Online publication date: 16-Oct-2023
  • (2023)White Cane-Type Holdable Device Using Illusory Pulling Cues for Orientation & Mobility TrainingIEEE Access10.1109/ACCESS.2023.325996511(28706-28714)Online publication date: 2023
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Information & Contributors

Information

Published In

cover image ACM Conferences
SIGGRAPH '20: ACM SIGGRAPH 2020 Emerging Technologies
August 2020
46 pages
ISBN:9781450379670
DOI:10.1145/3388534
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 August 2020

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Author Tags

  1. Force Feedback
  2. Golf-swing Training
  3. LSTM
  4. Trajectory Prediction

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  • Abstract
  • Research
  • Refereed limited

Funding Sources

  • JST CREST
  • JSPS KAKENHI

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SIGGRAPH '20
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Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

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Cited By

View all
  • (2023)AI Coach: A Motor Skill Training System using Motion Discrepancy DetectionProceedings of the Augmented Humans International Conference 202310.1145/3582700.3582710(179-189)Online publication date: 12-Mar-2023
  • (2023)Gino .Aiki: Mixed Reality-based Physical Motor Skill Training in Aikido2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)10.1109/ISMAR-Adjunct60411.2023.00112(519-524)Online publication date: 16-Oct-2023
  • (2023)White Cane-Type Holdable Device Using Illusory Pulling Cues for Orientation & Mobility TrainingIEEE Access10.1109/ACCESS.2023.325996511(28706-28714)Online publication date: 2023
  • (2022)Posture-based Golf Swing Instruction using Multi-modal FeedbackJournal of Information Processing10.2197/ipsjjip.30.10730(107-117)Online publication date: 2022

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