119 citations · 241 across the 27 of their papers we have counts for
28 papers
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…
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…
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…
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…
Graph-Based vs. Error State Kalman Filter-Based Fusion Of 5G And Inertial Data For MAV Indoor Pose Estimation
Meisam Kabiri, Claudio Cimarelli, Hriday Bavle +2
5G New Radio Time of Arrival (ToA) data has the potential to revolutionize indoor localization for micro aerial vehicles (MAVs). However, its performance under varying network setu…
UAV-assisted Visual SLAM Generating Reconstructed 3D Scene Graphs in GPS-denied Environments
Ahmed Radwan, Ali Tourani, Hriday Bavle +2
Aerial robots play a vital role in various applications where the situational awareness of the robots concerning the environment is a fundamental demand. As one such use case, dron…
Multi S-Graphs: An Efficient Distributed Semantic-Relational Collaborative SLAM
Miguel Fernandez-Cortizas, Hriday Bavle, David Perez-Saura +3
Collaborative Simultaneous Localization and Mapping (CSLAM) is critical to enable multiple robots to operate in complex environments. Most CSLAM techniques rely on raw sensor measu…
Learning High-level Semantic-Relational Concepts for SLAM
Jose Andres Millan-Romera, Hriday Bavle, Muhammad Shaheer +3
Recent works on SLAM extend their pose graphs with higher-level semantic concepts like Rooms exploiting relationships between them, to provide, not only a richer representation of…
Vision-based Situational Graphs Exploiting Fiducial Markers for the Integration of Semantic Entities
Ali Tourani, Hriday Bavle, Jose Luis Sanchez-Lopez +3
Situational Graphs (S-Graphs) merge geometric models of the environment generated by Simultaneous Localization and Mapping (SLAM) approaches with 3D scene graphs into a multi-layer…
Faster Optimization in S-Graphs Exploiting Hierarchy
Hriday Bavle, Jose Luis Sanchez-Lopez, Javier Civera +1
3D scene graphs hierarchically represent the environment appropriately organizing different environmental entities in various layers. Our previous work on situational graphs extend…
S-Nav: Semantic-Geometric Planning for Mobile Robots
Paul Kremer, Hriday Bavle, Jose Luis Sanchez-Lopez +1
Path planning is a basic capability of autonomous mobile robots. Former approaches in path planning exploit only the given geometric information from the environment without levera…
Pose Graph Optimization for a MAV Indoor Localization Fusing 5GNR TOA with an IMU
Meisam Kabiri, Claudio Cimarelli, Hriday Bavle +2
This paper explores the potential of 5G new radio (NR) Time-of-Arrival (TOA) data for indoor drone localization under different scenarios and conditions when fused with inertial me…
Graph-based Global Robot Simultaneous Localization and Mapping using Architectural Plans
Muhammad Shaheer, Jose Andres Millan-Romera, Hriday Bavle +3
In this paper, we propose a solution for graph-based global robot simultaneous localization and mapping (SLAM) using architectural plans. Before the start of the robot operation, t…
Multi S-graphs: A Collaborative Semantic SLAM architecture
Miguel Fernandez-Cortizas, Hriday Bavle, Jose Luis Sanchez-Lopez +2
Collaborative Simultaneous Localization and Mapping (CSLAM) is a critical capability for enabling multiple robots to operate in complex environments. Most CSLAM techniques rely on…
Marker-based Visual SLAM leveraging Hierarchical Representations
Ali Tourani, Hriday Bavle, Jose Luis Sanchez-Lopez +2
Fiducial markers can encode rich information about the environment and can aid Visual SLAM (VSLAM) approaches in reconstructing maps with practical semantic information. Current ma…
Graph-based Global Robot Localization Informing Situational Graphs with Architectural Graphs
Muhammad Shaheer, Jose Andres Millan-Romera, Hriday Bavle +3
In this paper, we propose a solution for legged robot localization using architectural plans. Our specific contributions towards this goal are several. Firstly, we develop a method…
S-Graphs+: Real-time Localization and Mapping leveraging Hierarchical Representations
Hriday Bavle, Jose Luis Sanchez-Lopez, Muhammad Shaheer +2
In this paper, we present an evolved version of Situational Graphs, which jointly models in a single optimizable factor graph (1) a pose graph, as a set of robot keyframes comprisi…
A Review of Radio Frequency Based Localization for Aerial and Ground Robots with 5G Future Perspectives
Meisam Kabiri, Claudio Cimarelli, Hriday Bavle +2
Efficient localization plays a vital role in many modern applications of Unmanned Ground Vehicles (UGV) and Unmanned aerial vehicles (UAVs), which would contribute to improved cont…
Advanced Situational Graphs for Robot Navigation in Structured Indoor Environments
Hriday Bavle, Jose Luis Sanchez-Lopez, Muhammad Shaheer +2
Mobile robots extract information from its environment to understand their current situation to enable intelligent decision making and autonomous task execution. In our previous wo…
Visual SLAM: What are the Current Trends and What to Expect?
Ali Tourani, Hriday Bavle, Jose Luis Sanchez-Lopez +1
Vision-based sensors have shown significant performance, accuracy, and efficiency gain in Simultaneous Localization and Mapping (SLAM) systems in recent years. In this regard, Visu…
Robot Localization using Situational Graphs and Building Architectural Plans
Muhammad Shaheer, Hriday Bavle, Jose Luis Sanchez-Lopez +1
Robots in the construction industry can reduce costs through constant monitoring of the work progress, using high precision data capturing. Accurate data capturing requires precise…