CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-horizon Robot Manipulation Tasks. (arXiv:2112.03227v3 [cs.RO] UPDATED)

Web: http://arxiv.org/abs/2112.03227

General-purpose robots coexisting with humans in their environment must learn
to relate human language to their perceptions and actions to be useful in a
range of daily tasks. Moreover, they need to acquire a diverse repertoire of
general-purpose skills that allow composing long-horizon tasks by following
unconstrained language instructions. In this paper, we present CALVIN
(Composing Actions from Language and Vision), an open-source simulated
benchmark to learn long-horizon language-conditioned tasks. Our aim is to make
it possible to develop agents …

arxiv benchmark language learning policy robot