Abstract
Identifying structural damage in confined spaces with restricted access, such as gas pipelines, poses a significant challenge. This work proposes a concept, that can tackle the challenges by using a visual Simultaneous Localization and Mapping (vSLAM) system consisting of a various combined sensors on a 3D printed platform. The integration of multiple sensors results in an accurate trajectory and mapping solution. Damage detection can be then achieved by Machine Learning (ML) algorithms trained on extracted point clouds.
| Originalsprache | Englisch |
|---|---|
| Titel | Proceedings of the 5th KuVS/GI Expert Talk on Localization |
| Redakteure/-innen | Marco Cimdins, Horst Hellbrück, Harald Sternberg |
| Erscheinungsort | Hamburg |
| Verlag | HafenCity Universität Hamburg |
| Seiten | 17-19 |
| Seitenumfang | 3 |
| Publikationsstatus | Veröffentlicht - 20 Juni 2024 |
| Veranstaltung | 5th Expert Talk on Localization - Lübeck, Deutschland Dauer: 6 Juni 2024 → 7 Juni 2024 |
Tagung/Konferenz
| Tagung/Konferenz | 5th Expert Talk on Localization |
|---|---|
| Land/Gebiet | Deutschland |
| Ort | Lübeck |
| Zeitraum | 6/06/24 → 7/06/24 |
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