FEAST is a mealtime assistance robot that uses LLM-editable behavior trees and modular tools to let care recipients personalize feeding, drinking, and mouth wiping in real home settings.
In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing
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abstract
Assistance during eating is essential for those with severe mobility issues or eating risks. However, dependence on traditional human caregivers is linked to malnutrition, weight loss, and low self-esteem. For those who require eating assistance, a semi-autonomous robotic platform can provide independence and a healthier lifestyle. We demonstrate an essential capability of this platform: safe, comfortable, and effective transfer of a bite-sized food item from a utensil directly to the inside of a person's mouth. Our system uses a force-reactive controller to safely accommodate the user's motions throughout the transfer, allowing full reactivity until bite detection then reducing reactivity in the direction of exit. Additionally, we introduce a novel dexterous wrist-like end effector capable of small, unimposing movements to reduce user discomfort. We conduct a user study with 11 participants covering 8 diverse food categories to evaluate our system end-to-end, and we find that users strongly prefer our method to a wide range of baselines. Appendices and videos are available at our website: https://tinyurl.com/btICRA.
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FEAST: A Flexible Mealtime-Assistance System Towards In-the-Wild Personalization
FEAST is a mealtime assistance robot that uses LLM-editable behavior trees and modular tools to let care recipients personalize feeding, drinking, and mouth wiping in real home settings.