activity
20232026
most citedOn Digital Twins in Defence: Overview and Applications

7 citations · 14 across the 23 of their papers we have counts for

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21 papers · 1 filter

cs.RO2026

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…

cs.RO2026

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…

cs.RO2026

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…

cs.RO2026

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…

cs.RO2025

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…

cs.RO2025

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…