Design and Evaluation of an Ultra-Low-Cost Admittance-Controlled Haptic Paddle
B. Aelbers (TU Delft - Mechanical Engineering)
A.H.A. Stienen – Mentor (TU Delft - Mechanical Engineering)
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Abstract
Stroke is a leading cause of long-term disability and frequently results in upper-limb motor impairments that reduce manual dexterity and quality of life. Robotic assessment systems have been developed to provide objective quantification of these impairments; however, their high cost limits accessibility, particularly in low- and middle-income countries where the majority of stroke cases occur. This thesis investigates the feasibility of implementing admittance control in an ultra-low-cost haptic device intended as a hand-module extension for robotic stroke assessment. A single-degree-of-freedom haptic paddle was developed using widely available components and a total hardware budget below €50. The device incorporates force and position sensing, a DC motor actuation system, and an Arduino-based control architecture. An admittance controller was implemented to render programmable virtual inertia, damping, and stiffness, while a PID position controller provided motion tracking. System performance was evaluated through step-response, frequency-response, and position-tracking experiments involving human interaction. The developed device successfully achieved stable admittance-controlled interaction and is capable of rendering a range of virtual dynamic environments. Experimental results demonstrated accurate position tracking, consistent rendering of virtual dynamics, and stable operation despite the sensing, bandwidth, and actuation limitations associated with low-cost hardware. The system is capable of reproducing meaningful changes in virtual inertia, damping, and stiffness while maintaining user controllability and interaction stability. These findings demonstrate that admittance control is feasible on an ultra-low-cost haptic platform. The proposed design provides a promising foundation for affordable rehabilitation and assessment technologies and supports the development of accessible robotic tools for objective evaluation of post-stroke motor impairments.