23 citations · 44 across the 28 of their papers we have counts for
30 papers
MVP-SLAM: Multi-Camera Visual-Inertial Floorplan-Prior SLAM
Asier Bikandi-Noya, Miguel Fernandez-Cortizas, Muhammad Shaheer +2
Indoor building construction sites are demanding environments for visual SLAM, where variable lighting and repetitive, low-textured structures make the system drift over long traje…
Generation of High-Level Concepts in 3D Scene Graphs via Autoregressive Diffusion
Jose Andres Millan-Romera, Samuel Cognolato, Holger Voos +2
Indoor 3D Scene Graphs (3DSGs) represent environments as multi-layer hierarchies that connect observed geometric primitives (e.g., planes) to higher-level metric-semantic concepts…
SUFLECA: Scaling Up Feature Learning for CAD-to-image Alignment
Saad Ejaz, Miguel Fernandez-Cortizas, Javier Civera +2
CAD-to-image alignment aims to estimate an object's 9D pose (rotation, translation, and anisotropic scale) from a single RGB image, with applications in robotics and augmented real…
Learning-Based Hierarchical Scene Graph Matching for Robot Localization Leveraging Prior Maps
Nimrod Millenium Ndulue, Jose Andres Millan-Romera, Matteo Giorgi +2
Accurate localization is a fundamental requirement for autonomous robots operating in indoor environments. Scene graphs encode the spatial structure of an environment as a hierarch…
Robust Graph Matching through Semantic Relationship Generation for SLAM
David Perez-Saura, Jose Andres Millan-Romera, Miguel Fernandez-Cortizas +3
Graph-based representations such as Scene Graphs enable localization in structured indoor environments by matching a locally observed graph, constructed from sensor data, to a prio…
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…
Passage-Aware Structural Mapping for RGB-D Visual SLAM
Ali Tourani, Miguel Fernandez-Cortizas, Saad Ejaz +4
Doorways and passages are critical structural elements for indoor robot navigation, yet they remain underexplored in modern Visual SLAM (VSLAM) frameworks. This paper presents a pa…
SMapper: A Multi-Modal Data Acquisition Platform for SLAM Benchmarking
Pedro Miguel Bastos Soares, Ali Tourani, Miguel Fernandez-Cortizas +3
Advancing research in fields such as Simultaneous Localization and Mapping (SLAM) and autonomous navigation critically depends on the availability of reliable and reproducible mult…
Human Interaction for Collaborative Semantic SLAM using Extended Reality
Laura Ribeiro, Muhammad Shaheer, Miguel Fernandez-Cortizas +3
Semantic SLAM (Simultaneous Localization and Mapping) systems enrich robot maps with structural and semantic information, enabling robots to operate more effectively in complex env…
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…
Interpretable Robot Control via Structured Behavior Trees and Large Language Models
Ingrid Maéva Chekam, Ines Pastor-Martinez, Ali Tourani +5
As intelligent robots become more integrated into human environments, there is a growing need for intuitive and reliable Human-Robot Interaction (HRI) interfaces that are adaptable…
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,…
On Digital Twins in Defence: Overview and Applications
Marco Giberna, Holger Voos, Paulo Tavares +4
Digital twins have emerged as a transformative technology for modeling and simulation in various industries, including defense. This paper provides a comprehensive review of digita…
Hardware, Algorithms, and Applications of the Neuromorphic Vision Sensor: a Review
Claudio Cimarelli, Jose Andres Millan-Romera, Holger Voos +1
Neuromorphic, or event, cameras represent a transformation in the classical approach to visual sensing encodes detected instantaneous per-pixel illumination changes into an asynchr…
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…
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…
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…
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,…
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…
Motion Control in Multi-Rotor Aerial Robots Using Deep Reinforcement Learning
Gaurav Shetty, Mahya Ramezani, Hamed Habibi +2
This paper investigates the application of Deep Reinforcement (DRL) Learning to address motion control challenges in drones for additive manufacturing (AM). Drone-based additive ma…
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…
Towards Localizing Structural Elements: Merging Geometrical Detection with Semantic Verification in RGB-D Data
Ali Tourani, Saad Ejaz, Hriday Bavle +2
RGB-D cameras supply rich and dense visual and spatial information for various robotics tasks such as scene understanding, map reconstruction, and localization. Integrating depth a…
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…
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…