Holder, Martin Friedrich ; Hellwig, Sven ; Winner, Hermann (2019)
Real-Time Pose Graph SLAM based on Radar.
2019 IEEE Intelligent Vehicles Symposium (IV). Paris, France (9-12 June 2019)
doi: 10.1109/IVS.2019.8813841
Konferenzveröffentlichung, Erstveröffentlichung
Kurzbeschreibung (Abstract)
This work presents a real-time pose graph based Simultaneous Localization and Mapping (SLAM) system for automotive Radar. The algorithm constructs a map from Radar detections using the Iterative Closest Point (ICP) method to match consecutive scans obtained from a single, front-facing Radar sensor. The algorithm is evaluated on a range of real-world datasets and shows mean translational errors as low as 0.62 m and demonstrates robustness on long tracks. Using a single Radar, our proposed system achieves state-of-the-art performance when compared to other Radar-based SLAM algorithms that use multiple, higher-resolution Radars.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2019 |
| Autor(en): | Holder, Martin Friedrich ; Hellwig, Sven ; Winner, Hermann |
| Art des Eintrags: | Erstveröffentlichung |
| Titel: | Real-Time Pose Graph SLAM based on Radar |
| Sprache: | Englisch |
| Publikationsjahr: | 2019 |
| Buchtitel: | 2019 IEEE Intelligent Vehicles Symposium (IV) |
| Veranstaltungstitel: | 2019 IEEE Intelligent Vehicles Symposium (IV) |
| Veranstaltungsort: | Paris, France |
| Veranstaltungsdatum: | 9-12 June 2019 |
| DOI: | 10.1109/IVS.2019.8813841 |
| URL / URN: | https://doi.org/10.1109/IVS.2019.8813841 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | This work presents a real-time pose graph based Simultaneous Localization and Mapping (SLAM) system for automotive Radar. The algorithm constructs a map from Radar detections using the Iterative Closest Point (ICP) method to match consecutive scans obtained from a single, front-facing Radar sensor. The algorithm is evaluated on a range of real-world datasets and shows mean translational errors as low as 0.62 m and demonstrates robustness on long tracks. Using a single Radar, our proposed system achieves state-of-the-art performance when compared to other Radar-based SLAM algorithms that use multiple, higher-resolution Radars. |
| URN: | urn:nbn:de:tuda-tuprints-92856 |
| Zusätzliche Informationen: | See https://tuprints.ulb.tu-darmstadt.de/8756/ for video attachment |
| Sachgruppe der Dewey Dezimalklassifikatin (DDC): | 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Fachgebiet Fahrzeugtechnik (FZD) 16 Fachbereich Maschinenbau > Fachgebiet Fahrzeugtechnik (FZD) > Fahrerassistenzssysteme |
| Hinterlegungsdatum: | 24 Nov 2019 20:55 |
| Letzte Änderung: | 23 Jun 2020 09:07 |
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| Zugehörige Links: | |
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