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024 7 _a10.1007/978-981-19-1972-5
_2doi
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082 0 4 _a629.892
_223
100 1 _aBędkowski, Janusz.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aLarge-Scale Simultaneous Localization and Mapping
_h[electronic resource] /
_cby Janusz Będkowski.
250 _a1st ed. 2022.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2022.
300 _aXVIII, 308 p. 204 illus., 174 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _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++ 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.
650 0 _aRobotics.
650 0 _aComputer science
_xMathematics.
650 0 _aComputer vision.
650 1 4 _aRobotics.
650 2 4 _aMathematical Applications in Computer Science.
650 2 4 _aComputer Vision.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811919718
776 0 8 _iPrinted edition:
_z9789811919732
776 0 8 _iPrinted edition:
_z9789811919749
830 0 _aCognitive Intelligence and Robotics,
_x2520-1964
856 4 0 _uhttps://doi.org/10.1007/978-981-19-1972-5
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c178316
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