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  • Vaidis, Maxime, et al. (author)
  • Extrinsic calibration for highly accurate trajectories reconstruction
  • 2023
  • In: 2023 IEEE International Conference on Robotics and Automation (ICRA). - : IEEE. - 9798350323658 - 9798350323665 ; , s. 4185-4192
  • Conference paper (peer-reviewed)abstract
    • In the context of robotics, accurate ground-truth positioning is the cornerstone for the development of mapping and localization algorithms. In outdoor environments and over long distances, total stations provide accurate and precise measurements, that are unaffected by the usual factors that deteriorate the accuracy of Global Navigation Satellite System (GNSS). While a single robotic total station can track the position of a target in three Degrees Of Freedom (DOF), three robotic total stations and three targets are necessary to yield the full six DOF pose reference. Since it is crucial to express the position of targets in a common coordinate frame, we present a novel extrinsic calibration method of multiple robotic total stations with field deployment in mind. The proposed method does not require the manual collection of ground control points during the system setup, nor does it require tedious synchronous measurement on each robotic total station. Based on extensive experimental work, we compare our approach to the classical extrinsic calibration methods used in geomatics for surveying and demonstrate that our approach brings substantial time savings during the deployment. Tested on more than 30 km of trajectories, our new method increases the precision of the extrinsic calibration by 25 % compared to the best state-of-the-art method, which is the one taking manually static ground control points.
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  • Result 1-1 of 1
Type of publication
conference paper (1)
Type of content
peer-reviewed (1)
Author/Editor
Kubelka, Vladimír, 1 ... (1)
Pomerleau, Francois (1)
Vaidis, Maxime (1)
Dubois, William (1)
Guénette, Alexandre (1)
Laconte, Johann (1)
University
Örebro University (1)
Language
English (1)
Research subject (UKÄ/SCB)
Natural sciences (1)
Year

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