7 papers
vS-Graphs: Tightly Coupling Visual SLAM and 3D Scene Graphs Exploiting Hierarchical Scene Understanding
Ali Tourani, Saad Ejaz, Hriday Bavle +4
Current Visual Simultaneous Localization and Mapping (VSLAM) systems often struggle to create maps that are both semantically rich and easily interpretable. While incorporating sem…
Unveiling the Potential of iMarkers: Invisible Fiducial Markers for Advanced Robotics
Ali Tourani, Deniz Isinsu Avsar, Hriday Bavle +3
Fiducial markers are widely used in robotics for navigation, object recognition, and scene understanding. While offering significant advantages for robots and Augmented Reality (AR…
BIM-Constrained Optimization for Accurate Localization and Deviation Correction in Construction Monitoring
Asier Bikandi-Noya, Muhammad Shaheer, Hriday Bavle +3
Augmented reality (AR) applications for construction monitoring rely on real-time environmental tracking to visualize architectural elements. However, construction sites present si…
S-Graphs 2.0 -- A Hierarchical-Semantic Optimization and Loop Closure for SLAM
Hriday Bavle, Jose Luis Sanchez-Lopez, Muhammad Shaheer +2
The hierarchical structure of 3D scene graphs shows a high relevance for representations purposes, as it fits common patterns from man-made environments. But, additionally, the sem…
Category-level Meta-learned NeRF Priors for Efficient Object Mapping
Saad Ejaz, Hriday Bavle, Laura Ribeiro +2
In 3D object mapping, category-level priors enable efficient object reconstruction and canonical pose estimation, requiring only a single prior per semantic category (e.g., chair,…
Tightly Coupled SLAM with Imprecise Architectural Plans
Muhammad Shaheer, Jose Andres Millan-Romera, Hriday Bavle +4
Robots navigating indoor environments often have access to architectural plans, which can serve as prior knowledge to enhance their localization and mapping capabilities. While som…