Landmark based radar SLAM using graph optimization
- On the way to achieving higher degrees of autonomy for vehicles in complicated, ever changing scenarios, the localization problem poses a very important role. Especially the Simultaneous Localization and Mapping (SLAM) problem has been studied greatly in the past. For an autonomous system in the real world, we present a very cost-efficient, robust and very precise localization approach based on GraphSLAM and graph optimization using radar sensors. We are able to prove on a dynamically changing parking lot layout that both mapping and localization accuracy are very high. To evaluate the performance of the mapping algorithm, a highly accurate ground truth map generated from a total station was used. Localization results are compared to a high precision DGPS/INS system. Utilizing these methods, we can show the strong performance of our algorithm.
| Author of HS Reutlingen | Curio, Cristóbal |
|---|---|
| DOI: | https://doi.org/10.1109/ITSC.2016.7795967 |
| ISBN: | 978-1-5090-1889-5 |
| Erschienen in: | IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Windsor Oceanico Hotel, Rio de Janeiro, Brazil, November 1-4, 2016 |
| Publisher: | IEEE |
| Place of publication: | Piscataway, NJ |
| Document Type: | Conference proceeding |
| Language: | English |
| Publication year: | 2016 |
| Page Number: | 6 |
| First Page: | 2559 |
| Last Page: | 2564 |
| DDC classes: | 620 Ingenieurwissenschaften und Maschinenbau |
| Open access?: | Nein |
| Licence (German): |  In Copyright - Urheberrechtlich geschützt |
