Synthesis and control of an assistive robotic tennis trainer
Abstract
While robotic guidance can improve ongoing performance of a motor task, several studies have found that it ultimately impairs motor learning. However, some recent studies found that the haptic demonstration of optimal timing, rather than movement magnitude, apparently transfers to participants trained with robotic guidance. Here, we describe the synthesis, design and control of a novel tendon-based haptic device able to apply different forms of physical guidance to train a task for which timing is the critical performance determinant: a forearm tennis stroke. We designed three guidance control strategies: a position controller to apply a fixed haptic guidance, a path controller with zero-force controller inside a safety tunnel around the desired trajectory to apply no guidance, and a guidance-as-needed controller to adapt the amount of support as training progresses. The controllers were experimentally tested and evaluation results are presented. The position controller was able to track the desired trajectory, with minimum errors. The path controller avoided leaving the tunnel, but the zero-force controller inside the tunnel allowed subjects to intend the task by themselves. Finally, the guidance-as-needed controller was able to modulate the guidance, allowing more autonomy to initiate the movements as training progressed, while limiting tracking and velocity errors.
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In the tennis-type task, three control concepts (position control, path control, guidance-as-needed) were implemented to investigate influence on task timing, but learning was not assessed.
“In the tennis-type task, three different control concepts were implemented-position control, path control, and guidance-as-needed controller-in order to investigate the influence of different haptic guidance concepts on task timing, whereby learning was not assessed (Marchal-Crespo et al., 2012).”
From Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review (2013) · cites this paper as Marchal-Crespo et al., 2012
Cites
Schmidt, R. A., & Bjork, R. A. (1992) · Psychological Science · doi:10.1111/j.1467-9280.1992.tb00029.x · Cited by 1,582 · cited 1× · see citing works
“However, a number of studies have found that physical guidance of movements does not aid motor learning and may in fact hamper it [5], [6].”
BackgroundHaptic guidance: experimental evaluation of a haptic training method for a perceptual motor skill
Feygin, D., Keehner, M., & Tendick, R. (2003) · Proceedings 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. HAPTICS 2002 · doi:10.1109/haptic.2002.998939 · Cited by 394 · see citing works
Emken, J. L., Benitez, R., & Reinkensmeyer, D. J. (2007) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-4-8 · Cited by 199 · see citing works
Haptic Guidance Improves the Visuo-Manual Tracking of Trajectories
Bluteau, J., Coquillart, S., Payan, Y., & Gentaz, E. (2008) · PLoS ONE · doi:10.1371/journal.pone.0001775 · Cited by 153 · see citing works
The effect of haptic guidance, aging, and initial skill level on motor learning of a steering task
Marchal-Crespo, L., McHughen, S., Cramer, S. C., & Reinkensmeyer, D. J. (2010) · Experimental Brain Research · doi:10.1007/s00221-009-2026-8 · Cited by 143 · see citing works
Self-citationPresentation- and test-trial effects on acquisition and retention of distance and location.
Hagman, J. D. (1983) · Journal of Experimental Psychology: Learning, Memory, and Cognition · doi:10.1037/0278-7393.9.2.334 · Cited by 50 · see citing works
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Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review
Sigrist, R., Rauter, G., Riener, R., & Wolf, P. (2013) · Psychonomic Bulletin & Review · doi:10.3758/s13423-012-0333-8 · Cited by 1,416 · see citing works
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- Authors
- Marchal-Crespo, L., Rauter, G., Wyss, D., von Zitzewitz, J., & Riener, R.
- Affiliations
- University of Zurich (CH)
- Venue
- 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)
- Publisher
- IEEE
- Published
- 2012-06
- Pages
- 355-360
- ISSN
- 2155-1774 (ISSN-L)
- OpenAlex
- W2079836588
- Cited by
- 20
- References
- 6
- Citations by year
- 2025: 2 · 2024: 1 · 2023: 2 · 2022: 3 · 2021: 2 · 2020: 1 · 2017: 1 · 2014: 1 · 2013: 5 · 2012: 1
- FWCI
- 6.32
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) (publishedVersion)
- BORIS (University Library Bern) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Teleoperation and Haptic Systems
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Keywords
- assistive robotics, haptic guidance, motor learning, trajectory tracking, adaptive guidance
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