2023-12-02-gordon23a.md

title	section	openreview	abstract	layout	series	publisher	issn	id	month	tex_title	firstpage	lastpage	page	order	cycles	bibtex_author	author	date	address	container-title	volume	genre	issued	pdf	extras
Towards General Single-Utensil Food Acquisition with Human-Informed Actions	Poster	UZpWSDA3tZJ	Food acquisition with common general-purpose utensils is a necessary component of robot applications like in-home assistive feeding. Learning acquisition policies in this space is difficult in part because any model will need to contend with extensive state and actions spaces. Food is extremely diverse and generally difficult to simulate, and acquisition actions like skewers, scoops, wiggles, and twirls can be parameterized in myriad ways. However, food’s visual diversity can belie a degree of physical homogeneity, and many foods allow flexibility in how they are acquired. Due to these facts, our key insight is that a small subset of actions is sufficient to acquire a wide variety of food items. In this work, we present a methodology for identifying such a subset from limited human trajectory data. We first develop an over-parameterized action space of robot acquisition trajectories that capture the variety of human food acquisition technique. By mapping human trajectories into this space and clustering, we construct a discrete set of 11 actions. We demonstrate that this set is capable of acquiring a variety of food items with $\geq80%$ success rate, a rate that users have said is sufficient for in-home robot-assisted feeding. Furthermore, since this set is so small, we also show that we can use online learning to determine a sufficiently optimal action for a previously-unseen food item over the course of a single meal.	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	gordon23a	0	Towards General Single-Utensil Food Acquisition with Human-Informed Actions	2414	2428	2414-2428	2414	false	Gordon, Ethan Kroll and Nanavati, Amal and Challa, Ramya and Zhu, Bernie Hao and Faulkner, Taylor Annette Kessler and Srinivasa, Siddhartha	given family Ethan Kroll Gordon given family Amal Nanavati given family Ramya Challa given family Bernie Hao Zhu given family Taylor Annette Kessler Faulkner given family Siddhartha Srinivasa	2023-12-02		Proceedings of The 7th Conference on Robot Learning	229	inproceedings	date-parts 2023 12 2	https://proceedings.mlr.press/v229/gordon23a/gordon23a.pdf