9 papers
Generation of Uncertainty-Aware High-Level Spatial Concepts in Factorized 3D Scene Graphs via Graph Neural Networks
Jose Andres Millan-Romera, Muhammad Shaheer, Miguel Fernandez-Cortizas +3
Enabling robots to autonomously discover high-level spatial concepts (e.g., rooms and walls) from primitive geometric observations (e.g., planar surfaces) within 3D Scene Graphs is…
BIM Informed Visual SLAM for Construction Environments
Asier Bikandi-Noya, Miguel Fernandez-Cortizas, Muhammad Shaheer +3
Monitoring building construction sites requires comparing the as-planned design with the as-built state, which can be estimated in real time using Simultaneous Localization and Map…
COMPASS: COmpact Multi-channel Prior-map And Scene Signature for Floor-Plan-Based Visual Localization
Muhammad Shaheer, Miguel Fernandez-Cortizas, Asier Bikandi-Noya +2
Architectural floor plans are widely available priors which contain not only geometry but also the semantic information of the environment, yet existing localization methods largel…
Situationally-aware Path Planning Exploiting 3D Scene Graphs
Saad Ejaz, Marco Giberna, Muhammad Shaheer +5
3D Scene Graphs integrate both metric and semantic information, yet their structure remains underutilized for improving path planning efficiency and interpretability. In this work,…
DYNEMO-SLAM: Dynamic Entity and Motion-Aware 3D Scene Graph SLAM
Marco Giberna, Muhammad Shaheer, Miguel Fernandez-Cortizas +3
Robots operating in dynamic environments face significant challenges due to the presence of moving agents and displaced objects. Traditional SLAM systems typically assume a static…
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…