AdaDemo: Data-Efficient Demonstration Expansion for Generalist Robotic Agent

arXiv:2404.07428v1 Announce Type: cross
Abstract: Encouraged by the remarkable achievements of language and vision foundation models, developing generalist robotic agents through imitation learning, using large demonstration datasets, has become a prominent area of interest in robot learning. The efficacy of imitation learning is heavily reliant on the quantity and quality of the demonstration datasets. In this study, we aim to scale up demonstrations in a data-efficient way to facilitate the learning of generalist robotic agents. We introduce AdaDemo (Adaptive Online …

abstract agent agents arxiv become cs.lg cs.ro data datasets expansion foundation imitation learning language quality robot robotic through type vision