Indoor Localization and Mapping: Towards Tracking Resilience Through a Multi-SLAM Approach

Pierre Alliez (1) , Fabien Bonardi (2) , Samia Bouchafa (2) , Jean-Yves Didier (2) , Hicham Hadj-Abdelkader (2) , Fernando Israel Ireta Muñoz (1) , Viachaslau Kachurka (2) , Bastien Rault (3) , Maxime Robin (3) , David Roussel (2)

1 TITANE - Geometric Modeling of 3D Environments
2 IBISC - Informatique, BioInformatique, Systèmes Complexes
3 Innondura TB [Villeurbanne]

This paper presents a use case for SLAM techniques applied to real time localization and detailed mapping for emergency response personnel in non cooperative environments. Such environments tend to defeat conventional localization approaches, therefore we must ensure continuous operation of our localization and mapping regardless of the difficulties encountered (lack of GPS signals, lighting conditions, smoke, etc.). The proposed system fuses two SLAM algorithms, a LiDAR-based and a camera-based. Since LiDAR-based SLAM uses dense 3D measurements, it is well suited to the construction of a detailed map, while the visual SLAM allows to quickly recognize already visited places in order to apply loop closure corrections, by using a key frames graph. The currently proposed system allows collaboration between these two SLAMs through pose sharing and relocalization.

Domains: Electronics; Robotics [cs.RO]; Computer Vision and Pattern Recognition [cs.CV]; Graphics [cs.GR]; Embedded Systems

Pierre Alliez, Fabien Bonardi, Samia Bouchafa, Jean-Yves Didier, Hicham Hadj-Abdelkader, et al.. Indoor Localization and Mapping: Towards Tracking Resilience Through a Multi-SLAM Approach. MED 2020 - 28th Mediterranean Conference on Control and Automation, Sep 2020, Saint Raphael, France. pp.465--470. ⟨hal-02611679⟩