CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 11442 > Article
Open Access Paper
11 February 2020 LIDAR-based SLAM implementation using Kalman filter
Pawel Słowak, Piotr Kaniewski
Author Affiliations +
Proceedings Volume 11442, Radioelectronic Systems Conference 2019; 114420N (2020) https://doi.org/10.1117/12.2564818
Event: Radioelectronic Systems Conference 2019, 2019, Jachranka, Poland
Abstract
The capability to navigate accurately is one of the features, that a mobile robot should have to be able to perform tasks autonomously. In a GPS/GNSS-denied environment, for example inside buildings, localization of a mobile platform is an especially challenging problem. In such cases, to provide a robot with the ability to determine its position and to analyze its surroundings, Simultaneous Localization and Mapping (SLAM) algorithms could be implemented. In the article, we present a SLAM system that uses a Kalman filter together with data gathered by a 2D LiDAR. Our approach applies the ICP algorithm to calculate the localization and employs clustering and shape recognition technics to build the map of the environment. The article contains a detailed description of the individual elements of the proposed SLAM solution. Furthermore, it presents the results of experiments during which the system was validated.
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Pawel Słowak and Piotr Kaniewski "LIDAR-based SLAM implementation using Kalman filter", Proc. SPIE 11442, Radioelectronic Systems Conference 2019, 114420N (11 February 2020); https://doi.org/10.1117/12.2564818
PROCEEDINGS
 10 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Clouds
Filtering (signal processing)
Sensors
LIDAR
Detection and tracking algorithms
Buildings
Laser scanners
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top