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

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

arXiv.org Artificial Intelligence 

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.

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