2023-12-02-duan23a.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
AR2-D2: Training a Robot Without a Robot	Poster	JdpleC92J4	Diligently gathered human demonstrations serve as the unsung heroes empowering the progression of robot learning. Today, demonstrations are collected by training people to use specialized controllers, which (tele-)operate robots to manipulate a small number of objects. By contrast, we introduce AR2-D2: a system for collecting demonstrations which (1) does not require people with specialized training, (2) does not require any real robots during data collection, and therefore, (3) enables manipulation of diverse objects with a real robot. AR2-D2 is a framework in the form of an iOS app that people can use to record a video of themselves manipulating any object while simultaneously capturing essential data modalities for training a real robot. We show that data collected via our system enables the training of behavior cloning agents in manipulating real objects. Our experiments further show that training with our AR data is as effective as training with real-world robot demonstrations. Moreover, our user study indicates that users find AR2-D2 intuitive to use and require no training in contrast to four other frequently employed methods for collecting robot demonstrations.	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	duan23a	0	AR2-D2: Training a Robot Without a Robot	2838	2848	2838-2848	2838	false	Duan, Jiafei and Wang, Yi Ru and Shridhar, Mohit and Fox, Dieter and Krishna, Ranjay	given family Jiafei Duan given family Yi Ru Wang given family Mohit Shridhar given family Dieter Fox given family Ranjay Krishna	2023-12-02		Proceedings of The 7th Conference on Robot Learning	229	inproceedings	date-parts 2023 12 2	https://proceedings.mlr.press/v229/duan23a/duan23a.pdf