Robust Monte Carlo localization for mobile robots
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High-level visual judgments, such as whether an image contains an animal, can be computed within 150 ms.
“high-level visual judgments (e.g., whether an image contains an animal or not) could be computed within 150 ms.”
From Hierarchical Bayesian inference in the visual cortex (2003) · cites this paper as [14]
The paper’s §2.5 discusses a robot locating an object across multiple camera views, while §6.4 reports computation times for robot-localization algorithms. Searches for animal detection, high-level visual judgments, and 150 ms found no passage addressing the claimed judgment or its timing; page numbers were not available in our copy. (LLM, conf=0.77)
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- Authors
- Thrun, S., Fox, D., Burgard, W., & Dellaert, F.
- Affiliations
- Carnegie Mellon University (US)
- University of Washington (US)
- University of Freiburg (DE)
- Corresponding author
- Thrun, Sebastian
- Venue
- Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2001-05
- Volume
- 128
- Issue
- 1-2
- Pages
- 99-141
- ISSN
- 0004-3702 (ISSN-L)
- OpenAlex
- W2160584648
- Cited by
- 1,809
- References
- 1
- Citations by year
- 2026: 18 · 2025: 30 · 2024: 31 · 2023: 45 · 2022: 46 · 2021: 52 · 2020: 78 · 2019: 81 · 2018: 66 · 2017: 82 · 2016: 81 · 2015: 86 · 2014: 88 · 2013: 83 · 2012: 88
- FWCI
- 118.58
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Artificial Intelligence (publishedVersion)
- Defense Technical Information Center (DTIC) (submittedVersion)
- Funders
- National Science Foundation (9876136, 9877033, CAREER)
- Defense Advanced Research Projects Agency
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Physical Sciences › Computer Science › Artificial Intelligence › Target Tracking and Data Fusion in Sensor Networks
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Keywords
- Monte Carlo localization, mobile robot localization, probabilistic localization, Bayesian posterior approximation, weighted samples, rangefinder, robustness, computational efficiency
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