Joint calibration of Machine Vision subsystems for robuster surrounding 3D perception
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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.
Original language | English |
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Title of host publication | IECON 2024- 50th Annual Conference of the IEEE Industrial Electronics Society : Proceedings, Sheraton Grand Chicago Riverwalk Chicago, Illinois, USA 3 - 6 November 2024 |
Number of pages | 6 |
Place of Publication | Piscataway |
Publisher | IEEE Industrial Electronics Society |
Publication date | 2024 |
ISBN (print) | 978-1-6654-6455-0 |
ISBN (electronic) | 978-1-6654-6454-3 |
DOIs | |
Publication status | Published - 2024 |
Event | 50th Annual Conference of the IEEE Industrial Electronics Society - IECON 2024 - Chicago, United States Duration: 03.11.2024 → 06.11.2024 Conference number: 50 https://www.iecon-2024.org/ |
Bibliographical note
Publisher Copyright:
© 2024 IEEE.
- Control and Systems Engineering
- Electrical and Electronic Engineering
ASJC Scopus Subject Areas
- Artificial Vision, Calibration, Sensor Fusion
- Engineering