Scholarly record
DEVELOPMENT OF A MOBILE MAPPING SYSTEM FOR SIMULTANEOUS LOCALIZATION AND MAPPING
Abstract
The article deals with the developing and applying of the mobile mapping system developed at the Department of Surveying of the Slovak University of Technology in Bratislava. The article presents a low-cost mobile mapping system for simultaneous localization and mapping of the indoor environment. Existing systems are costly and have robust construction and high-power requirements, making them unavailable for some applications. The proposed measuring system consists of three orthogonally placed 2D lidars, a robotic platform with two rotary encoders, and an inertial measuring unit. The lidars scan the environment in three mutually perpendicular directions during the measurement. Based on the transformation between a pair of consecutive scans, the position of the system is updated. Then the model of the environment is updated using a new lidar scan. The estimated transformation parameters are translations expressing the change in position of the system and rotation, which represents the change in orientation of the measuring system. The errors in determining the transformation parameters represent the positioning errors, which are transmitted to the calculated model. For this reason, additional sensors are used (inertial measuring unit, speed sensors), based on which the error in position and orientation is corrected.
Publication Impact Profile
- Citations
- CrossRef - Citation Indexes: 1
- Scopus - Citation Indexes: 4
- Captures
- Mendeley - Readers: 3
Publication details
References10
CHEN, S. et al.: A LiDAR/Visual SLAM Backend with Loop Closure Detection and Graph Optimization. Remote Sensing. 2021, vol. 13, is. 14, p. 2720. DOI: 10.3390/rs13142720
CUMMINS, M. - NEWMAN, P.: Probabilistic appearance based navigation and loop closing. Proceedings 2007 IEEE International Conference on Robotics and Automation. 2007, pp. 2042-2048. ISSN 1050-4729. DOI: 10.1109/robot.2007.363622
BISTROM, B.: Comparative analysis of properties of LiDAR-based point clouds versus camera-based point clouds for 3D reconstruction using SLAM algorithms. 2019.
GUTMANN, J.S. - KONOLIGE, K.: Incremental mapping of large cyclic environments. In: Proceedings 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation. IEEE 1999, pp.318-325. ISBN 0-7803-5806-6 DOI: 10.1109/cira.1999.810068
VALENCIA, R. - ANDRADE-CETTO, J.: Mapping, planning and exploration with Pose SLAM. Berlin, Springer 2018, ISBN 978-3-319-60602-6. DOI: 10.1007/978-3-319-60603-3
THRUN, S. et al.: A system for volumetric robotic mapping of abandoned mines. In: 2003 IEEE International Conference on Robotics and Automation. IEEE 2003, pp. 4270-4275. ISBN 0-7803-7736-2. DOI: 10.1109/robot.2003.1242260
KUDRIASHOV, A. et al.: SLAM Techniques Application for Mobile Robot in Rough Terrain. Springer International Publishing 2020, ISBN 978-3-030-48980-9. DOI: 10.1007/978-3-030-48981-6
GRISETTI, G. et al.: A tutorial on graph-based SLAM. IEEE Intelligent Transportation Systems Magazine. 2010, vol. 2, is. 4, pp. 31-43. ISSN 1939-1390. DOI: 10.1109/mits.2010.939925
LU, F. - MILIOS, E.: Globally consistent range scan alignment for environment mapping. Autonomous robots. 1997, vol. 4, is. 4, pp. 333-349. DOI: 10.1023/a:1008854305733
PROKHOROV, D. et al.: Measuring robustness of Visual SLAM. In: 2019 16th International Conference on Machine Vision Applications (MVA). IEEE 2019, pp. 1-6. ISBN 978-1-7281-0925-1. DOI: 10.23919/mva.2019.8758020
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.