Details
| Originalsprache | Englisch |
|---|---|
| Seiten | 325-332 |
| Seitenumfang | 8 |
| Publikationsstatus | Veröffentlicht - 25 Mai 2023 |
| Veranstaltung | 12th International Symposium on Mobile Mapping Technology, MMT 2023 - Padua, Italien Dauer: 24 Mai 2023 → 26 Mai 2023 |
Konferenz
| Konferenz | 12th International Symposium on Mobile Mapping Technology, MMT 2023 |
|---|---|
| Land/Gebiet | Italien |
| Ort | Padua |
| Zeitraum | 24 Mai 2023 → 26 Mai 2023 |
Abstract
This paper proposes a voxel-based approach for creating a digital twin of an urban environment that is capable of efficiently managing smart spaces. The paper explains the registration and localization procedure of the point cloud dataset, which uses the KISS ICP for scan point cloud combination and the RANSAC method for the initial alignment of the combined point cloud. The mobile mapping point cloud using Riegl VMX-250 serves as the reference map, and Velodyne scans are used for localization purposes. The point-to-plane iterative closest-point method is then employed to refine the alignment. The paper evaluates the efficacy of the proposed method by calculating the errors between the estimated and ground truth positions. The results indicate that the voxel-based approach is capable of accurately estimating the position of the sensor platform, which are applicable for various use cases. A specific use case in the context is smart parking space management, which is described and initial visualization results are shown.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Information systems
- Sozialwissenschaften (insg.)
- Geografie, Planung und Entwicklung
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2023. 325-332 Beitrag in 12th International Symposium on Mobile Mapping Technology, MMT 2023, Padua, Italien.
Publikation: Konferenzbeitrag › Paper › Forschung › Peer-Review
}
TY - CONF
T1 - Voxel-Based Point Cloud Localization For Smart Spaces Management
AU - Mortazavi, F. S.
AU - Shkedova, O.
AU - Feuerhake, U.
AU - Brenner, C.
AU - Sester, M.
PY - 2023/5/25
Y1 - 2023/5/25
N2 - This paper proposes a voxel-based approach for creating a digital twin of an urban environment that is capable of efficiently managing smart spaces. The paper explains the registration and localization procedure of the point cloud dataset, which uses the KISS ICP for scan point cloud combination and the RANSAC method for the initial alignment of the combined point cloud. The mobile mapping point cloud using Riegl VMX-250 serves as the reference map, and Velodyne scans are used for localization purposes. The point-to-plane iterative closest-point method is then employed to refine the alignment. The paper evaluates the efficacy of the proposed method by calculating the errors between the estimated and ground truth positions. The results indicate that the voxel-based approach is capable of accurately estimating the position of the sensor platform, which are applicable for various use cases. A specific use case in the context is smart parking space management, which is described and initial visualization results are shown.
AB - This paper proposes a voxel-based approach for creating a digital twin of an urban environment that is capable of efficiently managing smart spaces. The paper explains the registration and localization procedure of the point cloud dataset, which uses the KISS ICP for scan point cloud combination and the RANSAC method for the initial alignment of the combined point cloud. The mobile mapping point cloud using Riegl VMX-250 serves as the reference map, and Velodyne scans are used for localization purposes. The point-to-plane iterative closest-point method is then employed to refine the alignment. The paper evaluates the efficacy of the proposed method by calculating the errors between the estimated and ground truth positions. The results indicate that the voxel-based approach is capable of accurately estimating the position of the sensor platform, which are applicable for various use cases. A specific use case in the context is smart parking space management, which is described and initial visualization results are shown.
KW - Digital twins
KW - ICP
KW - Localization
KW - Parking space management
KW - RANSAC
KW - Voxels
UR - http://www.scopus.com/inward/record.url?scp=85162143284&partnerID=8YFLogxK
U2 - 10.5194/isprs-archives-XLVIII-1-W1-2023-325-2023
DO - 10.5194/isprs-archives-XLVIII-1-W1-2023-325-2023
M3 - Paper
AN - SCOPUS:85162143284
SP - 325
EP - 332
T2 - 12th International Symposium on Mobile Mapping Technology, MMT 2023
Y2 - 24 May 2023 through 26 May 2023
ER -