Overview
- Provides all necessary observation equations for LiDAR, camera, motion model, and other constraints
- Gives programming examples for all observation equations
- Presents complementary methodology for large-scale mapping
Part of the book series: Cognitive Intelligence and Robotics (CIR)
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About this book
This book is dedicated for engineers and researchers who would like to increase the knowledge in area of mobile mapping systems. Therefore, the flow of the derived information is divided into subproblems corresponding to certain mobile mapping data and related observations’ equations. The proposed methodology is not fulfilling all SLAM aspects evident in the literature, but it is based on the experience within the context of the pragmatic and realistic applications. Thus, it can be supportive information for those who are familiar with SLAM and would like to have broader overview in the subject.
The novelty is a complete and interdisciplinary methodology for large-scale mobile mapping applications. The contribution is a set of programming examples available as supportive complementary material for this book. All observation equations are implemented, and for each, the programming example is provided. The programming examples are simple C++ implementationsthat can be elaborated by students or engineers; therefore, the experience in coding is not mandatory.
Moreover, since the implementation does not require many additional external programming libraries, it can be easily integrated with any mobile mapping framework. Finally, the purpose of this book is to collect all necessary observation equations and solvers to build computational system capable providing large-scale maps.
The novelty is a complete and interdisciplinary methodology for large-scale mobile mapping applications. The contribution is a set of programming examples available as supportive complementary material for this book. All observation equations are implemented, and for each, the programming example is provided. The programming examples are simple C++ implementationsthat can be elaborated by students or engineers; therefore, the experience in coding is not mandatory.
Moreover, since the implementation does not require many additional external programming libraries, it can be easily integrated with any mobile mapping framework. Finally, the purpose of this book is to collect all necessary observation equations and solvers to build computational system capable providing large-scale maps.
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Table of contents (12 chapters)
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Front Matter
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Introduction
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Front Matter
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Methodology
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Front Matter
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Observation Equations
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Front Matter
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Applications
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Front Matter
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Back Matter
Authors and Affiliations
About the author
Janusz Będkowski is D.Sc. and Ph.D. in mobile robotics. He is a researcher at Polish Academy of Science, Polish Academy of Science, Institute of Fundamental Technological Research, and engineer in TomTom International BV. He is actively working on the theoretical and practical aspects of simultaneous localization and mapping applications assuming global scale. Recently, he is working on the methodology of fulfilling the gap between geodesy and cartography, geo science and mobile robotics. He is active member of European Land Robotic Trial (ELROB) and the European Robotics Hackathon (ENRICH).
Bibliographic Information
Book Title: Large-Scale Simultaneous Localization and Mapping
Authors: Janusz Będkowski
Series Title: Cognitive Intelligence and Robotics
DOI: https://doi.org/10.1007/978-981-19-1972-5
Publisher: Springer Singapore
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022
Hardcover ISBN: 978-981-19-1971-8Published: 14 June 2022
Softcover ISBN: 978-981-19-1974-9Published: 15 June 2023
eBook ISBN: 978-981-19-1972-5Published: 13 June 2022
Series ISSN: 2520-1956
Series E-ISSN: 2520-1964
Edition Number: 1
Number of Pages: XVIII, 308
Number of Illustrations: 30 b/w illustrations, 174 illustrations in colour
Topics: Robotics, Mathematical Applications in Computer Science, Image Processing and Computer Vision