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Algorithmic Solutions for Computing Precise Maximum Likelihood 3D Point Clouds from Mobile Laser Scanning Platforms

Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-130478
  • Mobile laser scanning puts high requirements on the accuracy of the positioning systems and the calibration of the measurement system. We present a novel algorithmic approach for calibration with the goal of improving the measurement accuracy of mobile laser scanners. We describe a general framework for calibrating mobile sensor platforms that estimates all configuration parameters for any arrangement of positioning sensors, including odometry. In addition, we present a novel semi-rigid Simultaneous Localization and Mapping (SLAM) algorithmMobile laser scanning puts high requirements on the accuracy of the positioning systems and the calibration of the measurement system. We present a novel algorithmic approach for calibration with the goal of improving the measurement accuracy of mobile laser scanners. We describe a general framework for calibrating mobile sensor platforms that estimates all configuration parameters for any arrangement of positioning sensors, including odometry. In addition, we present a novel semi-rigid Simultaneous Localization and Mapping (SLAM) algorithm that corrects the vehicle position at every point in time along its trajectory, while simultaneously improving the quality and precision of the entire acquired point cloud. Using this algorithm, the temporary failure of accurate external positioning systems or the lack thereof can be compensated for. We demonstrate the capabilities of the two newly proposed algorithms on a wide variety of datasets.zeige mehrzeige weniger

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Metadaten
Autor(en): Jan Elseberg, Dorit Borrmann, Andreas Nüchter
URN:urn:nbn:de:bvb:20-opus-130478
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Fakultät für Mathematik und Informatik / Institut für Informatik
Sprache der Veröffentlichung:Englisch
Titel des übergeordneten Werkes / der Zeitschrift (Englisch):Remote Sensing
Erscheinungsjahr:2013
Band / Jahrgang:5
Heft / Ausgabe:11
Seitenangabe:5871-5906
Originalveröffentlichung / Quelle:Remote Sensing 2013, 5, 5871-5906; doi:10.3390/rs5115871
DOI:https://doi.org/10.3390/rs5115871
Allgemeine fachliche Zuordnung (DDC-Klassifikation):5 Naturwissenschaften und Mathematik / 52 Astronomie / 526 Mathematische Geografie
Freie Schlagwort(e):algorithms; calibration; mapping; mobile laser scanning; non-rigid registration
Datum der Freischaltung:07.07.2016
Lizenz (Deutsch):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung