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Poster
🏘️ ProcTHOR: Large-Scale Embodied AI Using Procedural Generation
Matt Deitke · Eli VanderBilt · Alvaro Herrasti · Luca Weihs · Kiana Ehsani · Jordi Salvador · Winson Han · Eric Kolve · Aniruddha Kembhavi · Roozbeh Mottaghi

Wed Nov 30 09:00 AM -- 11:00 AM (PST) @ Hall J #926

Massive datasets and high-capacity models have driven many recent advancements in computer vision and natural language understanding. This work presents a platform to enable similar success stories in Embodied AI. We propose ProcTHOR, a framework for procedural generation of Embodied AI environments. ProcTHOR enables us to sample arbitrarily large datasets of diverse, interactive, customizable, and performant virtual environments to train and evaluate embodied agents across navigation, interaction, and manipulation tasks. We demonstrate the power and potential of ProcTHOR via a sample of 10,000 generated houses and a simple neural model. Models trained using only RGB images on ProcTHOR, with no explicit mapping and no human task supervision produce state-of-the-art results across 6 embodied AI benchmarks for navigation, rearrangement, and arm manipulation, including the presently running Habitat 2022, AI2-THOR Rearrangement 2022, and RoboTHOR challenges. We also demonstrate strong 0-shot results on these benchmarks, via pre-training on ProcTHOR with no fine-tuning on the downstream benchmark, often beating previous state-of-the-art systems that access the downstream training data.

Author Information

Matt Deitke (Allen Institute for AI, University of Washington)
Matt Deitke

The first author of ProcTHOR (outstanding paper award winner at NeurIPS 2022).

Eli VanderBilt (University of Idaho)
Alvaro Herrasti (Allen Institute For Artificial Intelligence)
Luca Weihs (Allen Institute for Artificial Intelligence)
Kiana Ehsani (Allen Institute for Artificial Intelligence)
Jordi Salvador (Allen Institute for AI)
Winson Han
Eric Kolve (Allen Institute for Artificial Intelligence)
Aniruddha Kembhavi (Allen Institute for Artificial Intelligence (AI2))
Roozbeh Mottaghi (Meta)

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