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An Adaptable, Safe, and Portable Robot-Assisted Feeding System

Ethan Kroll Gordon, Rajat Kumar Jenamani, Amal Nanavati, Ziang Liu, Daniel Stabile, Xilai Dai, Tapomayukh Bhattacharjee, Tyler Schrenk, Jonathan Ko, Haya Bolotski, Raida Karim, A. Kashyap, Bernie Hao Zhu, Taylor Kessler Faulkner, Siddhartha S Srinivasa

Year
2024
Citations
19

Abstract

We demonstrate a robot-assisted feeding system that enables people with mobility impairments to feed themselves. Our system design embodies Safety, Portability, and User Control, with comprehensive full-stack safety checks, the ability to be mounted on and powered by any powered wheelchair, and a custom web-app allowing care-recipients to leverage their own assistive devices for robot control. For bite acquisition, we leverage multi-modal online learning to tractably adapt to unseen food types. For bite transfer, we leverage real-time mouth perception and interaction-aware control. Co-designed with community researchers, our system has been validated through multiple end-user studies.

Keywords

Software portabilityLeverage (statistics)Human–computer interactionComputer scienceRobotWheelchairEmbedded systemArtificial intelligenceWorld Wide WebOperating system

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