Benchmarking Augmentation Methods for Learning Robust Navigation Agents: the Winning Entry of the 2021 iGibson Challenge
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Benchmarking Augmentation Methods for Learning Robust Navigation Agents: the Winning Entry of the 2021 iGibson Challenge is a scholarly article[1].
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Benchmarking Augmentation Methods for Learning Robust Navigation Agents: the Winning Entry of the 2021 iGibson Challenge's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Benchmarking Augmentation Methods for Learning Robust Navigation Agents: the Winning Entry of the 2021 iGibson Challenge. Retrieved May 24, 2026, from https://4ort.xyz/entity/benchmarking-augmentation-methods-for-learning-robust-navigation-agents-the-winning-entry-of-the-2021-igibson-challenge
MLA“Benchmarking Augmentation Methods for Learning Robust Navigation Agents: the Winning Entry of the 2021 iGibson Challenge.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/benchmarking-augmentation-methods-for-learning-robust-navigation-agents-the-winning-entry-of-the-2021-igibson-challenge.
BibTeX@misc{4ortxyz_benchmarking-augmentation-methods-for-learning-robust-navigation-agents-the-winning-entry-of-the-2021-igibson-challenge_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Benchmarking Augmentation Methods for Learning Robust Navigation Agents: the Winning Entry of the 2021 iGibson Challenge}}, year = {2026}, url = {https://4ort.xyz/entity/benchmarking-augmentation-methods-for-learning-robust-navigation-agents-the-winning-entry-of-the-2021-igibson-challenge}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Benchmarking Augmentation Methods for Learning Robust Navigation Agents: the Winning Entry of the 2021 iGibson Challenge — https://4ort.xyz/entity/benchmarking-augmentation-methods-for-learning-robust-navigation-agents-the-winning-entry-of-the-2021-igibson-challenge (retrieved 2026-05-24)
