Training toddlers seated on mobile robots to drive indoors amidst obstacles
Abstract
The goal of this research is to train children seated on mobile robots to purposefully and safely drive indoors. Our previous studies show that in about six weeks of training, infants can learn to drive directly to a goal using conventional joysticks. However, they are unable to acquire the advanced skill to avoid obstacles while driving. This limits mobility impaired children from exploring their home environment safely, which in turn impacts their cognitive and social developments in the important early years. In this paper, we describe results where toddlers are trained to drive a robot within an obstacle course. Using algorithms based on artificial potential fields to avoid obstacles, we create force field on the joystick that trains them to navigate while avoiding obstacles. In this `assist-as-needed' approach, if the child steers the mobile robot outside a force tunnel centered around the desired direction, the driver experiences a bias force on the hand. The results suggest that force-feedback joystick results in faster learning than with a conventional joystick.
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All infants who received haptic feedback learned to drive through the maze more quickly and accurately than the control group.
“All infants who obtained haptic feedback learned to drive through the maze more quickly and more accurately than the control group.”
From Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review (2013) · cites this paper as Chen et al., 2010
In a maze task with developmentally delayed infants, haptic guidance by force fields displayed by a joystick was more effective than no haptic guidance.
“In a task that required developmentally delayed infants to find their way through a maze while sitting on a mobile robot, haptic guidance by force fields displayed by a joystick was also more effective than no haptic guidance (Chen et al., 2010).”
From Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review (2013) · cites this paper as Chen et al., 2010
Cites
Robot assisted gait training with Active Leg Exoskeleton (ALEX)
Banala, S. K., Kim, S. H., Agrawal, S. K., & Scholz, J. P. (2009) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2008.2008280 · Cited by 751 · see citing works
Haptic Guidance Can Enhance Motor Learning of a Steering Task
Crespo, L. M., & Reinkensmeyer, D. J. (2008) · Journal of Motor Behavior · doi:10.3200/jmbr.40.6.545-557 · Cited by 166 · cited 1× · see citing works
“In [22], a one-dimensional force with fading strength was implemented on a steering wheel to train adults to learn a steering task.”
MethodHaptic 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
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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
- Authors
- Chen, X., Ragonesi, C., Agrawal, S. K., & Galloway, J. C.
- Affiliations
- University of Delaware (US)
- Venue
- 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics
- Publisher
- IEEE
- Published
- 2010-09
- Volume
- 24
- Pages
- 576-581
- ISSN
- 2155-1774 (ISSN-L)
- OpenAlex
- W2029120442
- Cited by
- 8
- References
- 3
- Citations by year
- 2023: 1 · 2020: 1 · 2017: 1 · 2016: 1 · 2013: 1 · 2012: 3
- FWCI
- 2.52
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) (publishedVersion)
- Topics
- Health Sciences › Health Professions › Occupational Therapy › Assistive Technology in Communication and Mobility
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Engineering › Mechanical Engineering › Teleoperation and Haptic Systems
- Keywords
- toddlers, mobile robots, assistive mobility, obstacle avoidance, force feedback joystick, artificial potential field, indoor navigation, force fields
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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