CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks

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 fol...

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Vydané v:	IEEE robotics and automation letters Ročník 7; číslo 3; s. 7327 - 7334
Hlavní autori:	Mees, Oier, Hermann, Lukas, Rosete-Beas, Erick, Burgard, Wolfram Burgard
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.07.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Benchmark testing Benchmarks Cameras Data sets for robot learning Grippers Horizon imitation learning Language machine learning for robot control natural dialog for HRI Robot learning Robot sensing systems Robot vision systems Robots Task analysis Task complexity
ISSN:	2377-3766, 2377-3766
On-line prístup:	Získať plný text
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