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020			_a9789811919725
024	7		_a10.1007/978-981-19-1972-5 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aG70.212 _b2022 EB
100	1		_aBędkowski, Janusz _eautor _0(orcid)0000-0003-2630-1947 _1https://orcid.org/0000-0003-2630-1947 _4aut _4http://id.loc.gov/vocabulary/relators/aut _9685001
245	1	0	_aLarge-Scale Simultaneous Localization and Mapping _cby Janusz Będkowski
250			_aFirst edition 2022
264		1	_aSingapore _bSpringer International Publising _c2022
300			_a1 recurso en línea (XVIII, 308 páginas) _b204 ilustraciones, 174 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aCognitive Intelligence and Robotics _x2520-1964
505	0		_aChapter 1. Introduction -- Chapter 2. Terminology -- Chapter 3. Weighted Non Linear Least Square Optimization -- Chapter 4. Coordinate Systems -- Chapter 5. Mobile mapping data -- Chapter 6. Mobile Mapping Systems -- Chapter 7. Ground truth data sources -- Chapter 8. Trajectory estimation -- Chapter 9. Nearest observations search -- Chapter 10. Camera metrics -- Chapter 11. LiDAR metrics -- Chapter 12. Constraints -- Chapter 13. Metrics' fusion -- Chapter 14. Building large scale SLAM optimization -- Chapter 15. Loop closing and change detection -- Chapter 16. Final map qualitative and quantitative evaluation.
520			_aThis 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++ implementations that 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.
988			_aSpringer_Computer_2022
650		7	_2embne _9263853 _aSistemas de información geográfica
776	0	8	_iPrinted edition: _z9789811919718
776	0	8	_iPrinted edition: _z9789811919732
776	0	8	_iPrinted edition: _z9789811919749
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-19-1972-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b10/2022 _dz _eIG _zSI