The rise in mobility challenges due to aging populations has increased the need for innovative wheelchair technologies. Many users struggle with traditional power wheelchairs, finding them unusable and experiencing difficulties in steering. The solution, proposed by the author, is a novel side-by-side and hands-free Human-Machine Interface (HMI) for an omnidirectional electric wheelchair. It is designed to use a vision-based interface, with cameras capturing the head and torso movements of both the rider and a caregiver. Their motion intentions are interpreted and combined through shared control to produce velocity commands, enabling intuitive and collaborative navigation. This paper focuses on the hands-free HMI working principle. It analyzes how detects and processes the movements of the rider. The inputs are translated into linear and angular velocities relative to the wheelchair base, allowing navigation without using hands. Simulations validate the interface’s ability to drive the wheelchair smoothly around obstacles, aligning commands with user intentions. The system offers adjustable sensitivity to accommodate different movement thresholds to generate velocities.
Motion Tracking Hands-Free HMI of Electric Wheelchair
Mechan. Machine Science
International Workshop IFToMM for Sustainable Development Goals ; 2025 ; Lamezia Terme, Italy June 09, 2025 - June 11, 2025
Proceedings of I4SDG Workshop 2025 - IFToMM for Sustainable Development Goals ; Kapitel : 20 ; 181-189
22.05.2025
9 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Head gesture recognition for hands-free control of an intelligent wheelchair
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