In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing
Shaikewitz, Lorenzo, Wu, Yilin, Belkhale, Suneel, Grannen, Jennifer, Sundaresan, Priya, Sadigh, Dorsa
–arXiv.org Artificial Intelligence
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. To feed the user, it follows an arced trajectory and monitors force to detect a bite.
arXiv.org Artificial Intelligence
Mar-10-2023
- Genre:
- Research Report
- Experimental Study (1.00)
- New Finding (0.88)
- Research Report
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- Information Technology > Artificial Intelligence > Robots (1.00)