• Gyrevento: Event-based Omnidir...

Treffer: Gyrevento: Event-based Omnidirectional Visual Gyroscope in a Manhattan World

Title:
Gyrevento: Event-based Omnidirectional Visual Gyroscope in a Manhattan World
Authors:
da Costa, Daniel Rodrigues, Vasseur, Pascal, Morbidi, Fabio
Contributors:
Modélisation, Information et Systèmes - UR UPJV 4290 (MIS), Université de Picardie Jules Verne (UPJV), This work was supported by AID (Agence de l’Innovation de Défense), through the research project EVENTO, "Omnidirectional Event Cameras for High-Speed Robots" (2021-2024)., ANR-23-CE33-0011,EVELOC,Localisation visuelle basée évènements(2023)
Source:
IEEE Robotics and Automation Letters. 10(3):2910-2917
Publisher Information:
CCSD; IEEE, 2025.
Publication Year:
2025
Collection:
collection:UNIV-PICARDIE
collection:UPJV-MIS-PR
collection:ANR
collection:U-PICARDIE
collection:MIS
Subject Terms:
Event cameras, Omnidirectional Cameras, Attitude estimation, Mobile robot navigation, [INFO]Computer Science [cs], [INFO.INFO-CV]Computer Science [cs], Computer Vision and Pattern Recognition [cs.CV], [INFO.INFO-RB]Computer Science [cs], Robotics [cs.RO]
Original Identifier:
HAL: hal-04849696
Document Type:
Zeitschrift article<br />Journal articles
Language:
English
ISSN:
2377-3766
Relation:
info:eu-repo/semantics/altIdentifier/doi/10.1109/lra.2025.3527311
DOI:
10.1109/lra.2025.3527311
Access URL:
https://hal.science/hal-04849696
https://hal.science/hal-04849696v3/document
https://hal.science/hal-04849696v3/file/RoVaMo_RAL25.pdf
Rights:
info:eu-repo/semantics/OpenAccess
URL: http://hal.archives-ouvertes.fr/licences/copyright/
Accession Number:
edshal.hal.04849696v3
Database:
HAL

Weitere Informationen

In this paper, we study the problem of estimating the orientation of an event omnidirectional camera mounted on a robot and observing 3D parallel lines in a man-made environment (Manhattan world). We present Gyrevento, the first event-based omnidirectional visual gyroscope. Gyrevento does not require any initialization, provides certifiably globally optimal solutions, and is scalable, since the size of the nonlinear least-squares cost function is independent of the number of lines. Thanks to theCayley-Gibbs-Rodrigues parameterization of a 3D rotation, this cost function is a degree-four rational function in three variables, which can be efficiently minimized via off-the-shelf polynomial optimization software. Numerical simulations and real-world experiments with a robot manipulator show the effectiveness of our visual gyroscope and elucidate the impact of camera velocity on the attitude estimation error.