A Contextual Bandit Approach for Learning to Plan in Environ…
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Work Details
- DOI 10.1109/icra48891.2023.10160473
- OpenAlex ID W4383108416
- Type Conference-paper
- Language EN
- Published 29 May 2023
- Pages 5645–5652
- Source Proceedings - IEEE International Confere…
- Publisher Institute of Electrical and Electro…
- FWCI 1.06
- Countries 1
- Institutions 1
- Added 05 Jul 2023
- Updated 29 Oct 2026
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A Contextual Bandit Approach for Learning to Plan in Environments with Probabilistic Goal Configurations
Conference-paper 2023 EN Green
Object-goal navigation (Object-nav) entails searching, recognizing and navigating to a target object. Object-nav has been extensively studied by the Embodied-AI community, but most solutions are often restricted to considering static objects (e.g., television, fridge, etc.), We propose a modular framework for object-nav that is able to efficiently search indoor environments for not just static obj…
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1.06
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9 authors| # | Author | Institutions | ORCID |
|---|---|---|---|
| 1 | Sohan Rudra | Google (United States) (US) | — |
| 2 | Saksham Goel | Google (United States) (US) | |
| 3 | Anirban Santara | Google (United States) (US) | |
| 4 | Claudio Gentile | Google (United States) (US) | |
| 5 | Laurent Perron | Google (United States) (US) | — |
| 6 | Fei Xia | Google (United States) (US) | |
| 7 | Vikas Sindhwani | Google (United States) (US) | — |
| 8 | Carolina Parada | Google (United States) (US) | |
| 9 | Gaurav Aggarwal | Google (United States) (US) |
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