Joint calibration of Machine Vision subsystems for robuster surrounding 3D perception
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
Authors
To achieve successful autonomous navigation, a vision system that provides continuous and precise three-dimensional data of the system’s surroundings is always needed. An indispensable step in the acquisition of reliable data is the calibration of the system, preferably with a time-efficient and low-complexity approach. In this paper, a robust and efficient calibration method is proposed for the information fusion of a stereo vision system and a Technical Vision System. The proposed methodology achieves an error of xe = 6.9401 mm, ye = 8.0997 mm and ze = 15.1822 mm in 3.0202 seconds of processing time, as proven through experimental results.
Originalsprache | Englisch |
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Titel | IECON 2024- 50th Annual Conference of the IEEE Industrial Electronics Society : Proceedings, Sheraton Grand Chicago Riverwalk Chicago, Illinois, USA 3 - 6 November 2024 |
Anzahl der Seiten | 6 |
Erscheinungsort | Piscataway |
Verlag | IEEE Industrial Electronics Society |
Erscheinungsdatum | 2024 |
ISBN (Print) | 978-1-6654-6455-0 |
ISBN (elektronisch) | 978-1-6654-6454-3 |
DOIs | |
Publikationsstatus | Erschienen - 2024 |
Veranstaltung | 50th Annual Conference of the IEEE Industrial Electronics Society - IECON 2024 - Chicago, USA / Vereinigte Staaten Dauer: 03.11.2024 → 06.11.2024 Konferenznummer: 50 https://www.iecon-2024.org/ |
Bibliographische Notiz
Publisher Copyright:
© 2024 IEEE.
- Steuerungs- und Systemtechnik
- Elektrotechnik und Elektronik
ASJC Scopus Sachgebiete
- Artificial vision, Calibration, Sensor Fusion
- Ingenieurwissenschaften