What is recorded here?
Presented Monte Carlo localization, a sample-based probabilistic method that represents a mobile robot’s belief over position with weighted samples and updates it from motion and sensor evidence.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
The record is the exact four-author 1999 AAAI paper. It does not absorb particle filtering generally, simultaneous localization and mapping, later adaptive-sampling variants or every robot system using Monte Carlo localization.
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People and systems
Dieter Fox; Wolfram Burgard; Frank Dellaert; Sebastian Thrun
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.
Research locations and affiliations
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Documented countries / regions: United States, Germany
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English catalogue narrative
Fox, Burgard, Dellaert and Thrun: Monte Carlo localization
Presented Monte Carlo localization, a sample-based probabilistic method that represents a mobile robot’s belief over position with weighted samples and updates it from motion and sensor evidence.
Scientific scope
The record is the exact four-author 1999 AAAI paper. It does not absorb particle filtering generally, simultaneous localization and mapping, later adaptive-sampling variants or every robot system using Monte Carlo localization.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Dieter Fox; Wolfram Burgard; Frank Dellaert; Sebastian Thrun
The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.