Algorithms for Mobile Robot Localization and Mapping, Incorporating Detailed Noise Modeling and Multi-scale Feature Extraction

Algorithms for Mobile Robot Localization and Mapping, Incorporating Detailed Noise Modeling and Multi-scale Feature Extraction

<p>Mobile robot localization and mapping in unknown environments is a fundamental requirement for effective autonomous navigation. Three different approaches to localization and mapping are presented. Each is based on data collected from a robot using a dense range scanner to generate a plan...

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Bibliographic Details
Main Author: Pfister, Samuel Thomas
Format: Others
Published: 2006
Online Access:https://thesis.library.caltech.edu/2110/1/pfister_thesis_full.pdf
Pfister, Samuel Thomas (2006) Algorithms for Mobile Robot Localization and Mapping, Incorporating Detailed Noise Modeling and Multi-scale Feature Extraction. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/FN3J-M568. https://resolver.caltech.edu/CaltechETD:etd-05262006-130209 <https://resolver.caltech.edu/CaltechETD:etd-05262006-130209>

Internet

https://thesis.library.caltech.edu/2110/1/pfister_thesis_full.pdf
Pfister, Samuel Thomas (2006) Algorithms for Mobile Robot Localization and Mapping, Incorporating Detailed Noise Modeling and Multi-scale Feature Extraction. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/FN3J-M568. https://resolver.caltech.edu/CaltechETD:etd-05262006-130209 <https://resolver.caltech.edu/CaltechETD:etd-05262006-130209>

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