Algorithmic Solutions for Computing Precise Maximum Likelihood 3D Point Clouds from Mobile Laser Scanning Platforms
Please always quote using this 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.…
Author: | Jan Elseberg, Dorit Borrmann, Andreas Nüchter |
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URN: | urn:nbn:de:bvb:20-opus-130478 |
Document Type: | Journal article |
Faculties: | Fakultät für Mathematik und Informatik / Institut für Informatik |
Language: | English |
Parent Title (English): | Remote Sensing |
Year of Completion: | 2013 |
Volume: | 5 |
Issue: | 11 |
Pagenumber: | 5871-5906 |
Source: | Remote Sensing 2013, 5, 5871-5906; doi:10.3390/rs5115871 |
DOI: | https://doi.org/10.3390/rs5115871 |
Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 52 Astronomie / 526 Mathematische Geografie |
Tag: | algorithms; calibration; mapping; mobile laser scanning; non-rigid registration |
Release Date: | 2016/07/07 |
Licence (German): | CC BY: Creative-Commons-Lizenz: Namensnennung |