11 citations · 14 across the 10 of their papers we have counts for
11 papers
Scalix: Uncertainty-Aware Scale-Consistent Monocular SLAM
Sebastian Barbas Laina, Tianyi Zhang, Panagiotis Petropoulakis +5
Cameras are ubiquitous sensors in robotics due to their compact form factor and the perceptual richness captured through visual information. Monocular SLAM enables robots to unders…
AERO-VIS: Asynchronous Event-based Real-time Onboard Visual-Inertial SLAM
Yannick Burkhardt, Sebastián Barbas Laina, Simon Boche +2
The robustness of event cameras to high dynamic range and motion blur holds the potential to improve visual odometry systems in challenging environments. Although their high tempor…
OKVIS2-X: Open Keyframe-based Visual-Inertial SLAM Configurable with Dense Depth or LiDAR, and GNSS
Simon Boche, Jaehyung Jung, Sebastián Barbas Laina +1
To empower mobile robots with usable maps as well as highest state estimation accuracy and robustness, we present OKVIS2-X: a state-of-the-art multi-sensor Simultaneous Localizatio…
CoRe-GS: Coarse-to-Refined Gaussian Splatting with Semantic Object Focus
Hannah Schieber, Dominik Frischmann, Victor Schaack +4
Fast and efficient photorealistic 3D reconstruction with (semantic) Gaussian Splatting (GS) is crucial for time-critical robotic perception and navigation, where robots may need to…
FindAnything: Open-Vocabulary and Object-Centric Mapping for Robot Exploration in Any Environment
Sebastián Barbas Laina, Simon Boche, Sotiris Papatheodorou +4
Geometrically accurate and semantically expressive map representations have proven invaluable for robot deployment and task planning in unknown environments. Nevertheless, real-tim…
REGRACE: A Robust and Efficient Graph-based Re-localization Algorithm using Consistency Evaluation
Débora N. P. Oliveira, Joshua Knights, Sebastián Barbas Laina +3
Loop closures are essential for correcting odometry drift and creating consistent maps, especially in the context of large-scale navigation. Current methods using dense point cloud…
Efficient Submap-based Autonomous MAV Exploration using Visual-Inertial SLAM Configurable for LiDARs or Depth Cameras
Sotiris Papatheodorou, Simon Boche, Sebastián Barbas Laina +1
Autonomous exploration of unknown space is an essential component for the deployment of mobile robots in the real world. Safe navigation is crucial for all robotics applications an…
Uncertainty-Aware Visual-Inertial SLAM with Volumetric Occupancy Mapping
Jaehyung Jung, Simon Boche, Sebastián Barbas Laina +1
We propose visual-inertial simultaneous localization and mapping that tightly couples sparse reprojection errors, inertial measurement unit pre-integrals, and relative pose factors…
Tightly-Coupled LiDAR-Visual-Inertial SLAM and Large-Scale Volumetric Occupancy Mapping
Simon Boche, Sebastián Barbas Laina, Stefan Leutenegger
Autonomous navigation is one of the key requirements for every potential application of mobile robots in the real-world. Besides high-accuracy state estimation, a suitable and glob…
Scalable Outdoors Autonomous Drone Flight with Visual-Inertial SLAM and Dense Submaps Built without LiDAR
Sebastián Barbas Laina, Simon Boche, Sotiris Papatheodorou +4
Autonomous navigation is needed for several robotics applications. In this paper we present an autonomous Micro Aerial Vehicle (MAV) system which purely relies on cost-effective an…
Visual-Inertial SLAM with Tightly-Coupled Dropout-Tolerant GPS Fusion
Simon Boche, Xingxing Zuo, Simon Schaefer +1
Robotic applications are continuously striving towards higher levels of autonomy. To achieve that goal, a highly robust and accurate state estimation is indispensable. Combining vi…