An Autonomous Robotic Arm Enabling Independent Eating for Motor-Impaired Individuals

Overview

Over eleven million people worldwide live with Parkinson's disease or similar motor impairments, which can limit independent eating, yet commercial feeding devices cost over $5,000 and lack portability for daily use. We designed and validated a deployable, tabletop 4-DOF robotic feeding arm that enables independent feeding at under $300. A lightweight 3D-printed architecture reduces distal mass and actuator load, while a modular utensil mount and a custom plate with passive wiping features and spill guards minimize dripping. A monocular RGB camera feeds a real-time facial landmark model that estimates mouth pose and openness with 99.5% accuracy, utilizing motion-threshold gating to classify bite intent into four states: ready, wait, refuse, and reposition. Inverse kinematics continuously computes joint angles while preserving spoon orientation within ±3.5° across the full range of motion. Time-parametrized trajectory interpolation reduces velocity by 86% near the user’s face, ensuring smooth deceleration for safety and comfort. EMA-smoothed eye-width measurements calibrate approach distance to within 0.5 inches, while Kalman filtering reduces mouth tracking error by 56% and tracking latency by 75%. Food retrieval from user-selected plate regions is controlled via button input. System validation across 200 trials demonstrated stable mouth tracking under dynamic head motion, with consistent food placement within 0.2 inches of the mouth center and spill-free delivery in 96% of trials. These results demonstrate that a low-cost robotic feeding system can reliably track user motion and deliver food accurately, supporting the feasibility of accessible assistive robotics for restoring feeding independence.

Competition history

• CSEF 2026 Applied Mechanics (Senior Division) · Entry S-02-15

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