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CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-horizon Robot Manipulation Tasks. (arXiv:2112.03227v3 [cs.RO] UPDATED)
June 24, 2022, 1:12 a.m. | Oier Mees, Lukas Hermann, Erick Rosete-Beas, Wolfram Burgard
cs.CL updates on arXiv.org arxiv.org
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 …
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