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Lie Group Modelling for an EKF-Based Monocular SLAM Algorithm

Labsir, Samy and Pagès, Gaël and Vivet, Damien Lie Group Modelling for an EKF-Based Monocular SLAM Algorithm. (2022) Remote Sensing, 14 (3). 571. ISSN 2072-4292

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Official URL: https://doi.org/10.3390/rs14030571

Abstract

This paper addresses the problem of monocular Simultaneous Localization And Mapping on Lie groups using fiducial patterns. For that purpose, we propose a reformulation of the classical camera model as a model on matrix Lie groups. Thus, we define an original-state vector containing the camera pose and the set of transformations from the world frame to each pattern, which constitutes the map’s state. Each element of the map’s state, as well as the camera pose, are intrinsically constrained to evolve on the matrix Lie group SE(3). Filtering is then performed by an extended Kalman filter dedicated to matrix Lie groups to solve the visual SLAM process (LG-EKF-VSLAM). This algorithm has been evaluated in different scenarios based on simulated data as well as real data. The results show that the LG-EKF-VSLAM can improve the absolute position and orientation accuracy, compared to a classical EKF visual SLAM (EKF-VSLAM).

Item Type:Article
HAL Id:hal-03549470
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
Other partners > Thales (FRANCE)
Laboratory name:
Funders:
DGA/AID
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Deposited On:31 Jan 2022 13:05

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