Today, we're announcing new advances in embodied AI research to better understand & navigate physical and virtual worlds. https://t.co/7bAAI7qOUX
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We've developed the first plug-and-play modular approach that helps robots generalize to a diverse set of semantic navigation tasks and goal modalities — without retraining — in a novel zero-shot experience learning framework. https://t.co/krraCrQUbW https://t.co/lgTVwAxXH8
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And we’re continuing to push for efficiency with a novel formulation for object-goal navigation tasks using PONI that obtains state-of-the-art results while achieving a 1,600x reduction in training time compared with prior methods. https://t.co/92Bkz8l3Mi https://t.co/U1TpidBJnn
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To further improve training without reliance on maps, we’ve created and released Habitat-Web, a training data collection of over 100K different human demonstrations for object-goal navigation methods. https://t.co/dOOJ0CexhU https://t.co/FqbOfGlIgn
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