  Robot-assisted feeding can greatly enhance the lives of those with mobility
limitations. Modern feeding systems can pick up and position food in front of a
care recipient's mouth for a bite. However, many with severe mobility
constraints cannot lean forward and need direct inside-mouth food placement.
This demands precision, especially for those with restricted mouth openings,
and appropriately reacting to various physical interactions - incidental
contacts as the utensil moves inside, impulsive contacts due to sudden muscle
spasms, deliberate tongue maneuvers by the person being fed to guide the
utensil, and intentional bites. In this paper, we propose an inside-mouth bite
transfer system that addresses these challenges with two key components: a
multi-view mouth perception pipeline robust to tool occlusion, and a control
mechanism that employs multimodal time-series classification to discern and
react to different physical interactions. We demonstrate the efficacy of these
individual components through two ablation studies. In a full system
evaluation, our system successfully fed 13 care recipients with diverse
mobility challenges. Participants consistently emphasized the comfort and
safety of our inside-mouth bite transfer system, and gave it high technology
acceptance ratings - underscoring its transformative potential in real-world
scenarios. Supplementary materials and videos can be found at
http://emprise.cs.cornell.edu/bitetransfer/ .
