73 citations · 88 across the 7 of their papers we have counts for
11 papers
Attention-based Hierarchical Variational Information Bottleneck for Robust Multi-Agent Communication under Variable Bandwidth
Lukas Koch Vindbjerg, Qi Zhang, Yury Brodskiy +1
Learning-based multi-agent communication under limited bandwidth does not only require deciding what to communicate, but also structuring messages so that partial transmissions rem…
SeaVis: Modeling and Control of a Remotely Operated Towed Vehicle for Seabed Visualization and Mapping
Abdelhakim Amer, Aske Alstrup, Frederik Rasmussen +3
High-resolution seafloor mapping necessitates stable and precise positioning for underwater robots. This paper introduces a novel mathematical model for SeaVis remotely operated to…
REACT: Real-time Entanglement-Aware Coverage Path Planning for Tethered Underwater Vehicles
Abdelhakim Amer, Mohit Mehindratta, Yury Brodskiy +2
Inspection of underwater structures with tethered underwater vehicles is often hindered by the risk of tether entanglement. We propose REACT (real-time entanglement-aware coverage…
Modelling of Underwater Vehicles using Physics-Informed Neural Networks with Control
Abdelhakim Amer, David Felsager, Yury Brodskiy +1
Physics-informed neural networks (PINNs) integrate physical laws with data-driven models to improve generalization and sample efficiency. This work introduces an open-source implem…
Monocular visual simultaneous localization and mapping: (r)evolution from geometry to deep learning-based pipelines
Olaya Alvarez-Tunon, Yury Brodskiy, Erdal Kayacan
With the rise of deep learning, there is a fundamental change in visual SLAM algorithms toward developing different modules trained as end-to-end pipelines. However, regardless of…
Uncertainty Driven Active Learning for Image Segmentation in Underwater Inspection
Luiza Ribeiro Marnet, Yury Brodskiy, Stella Grasshof +1
Active learning aims to select the minimum amount of data to train a model that performs similarly to a model trained with the entire dataset. We study the potential of active lear…
Mission Planning and Safety Assessment for Pipeline Inspection Using Autonomous Underwater Vehicles: A Framework based on Behavior Trees
Martin Aubard, Sergio Quijano, Olaya Álvarez-Tuñón +3
The recent advance in autonomous underwater robotics facilitates autonomous inspection tasks of offshore infrastructure. However, current inspection missions rely on predefined pla…
SubPipe: A Submarine Pipeline Inspection Dataset for Segmentation and Visual-inertial Localization
Olaya Álvarez-Tuñón, Luiza Ribeiro Marnet, László Antal +3
This paper presents SubPipe, an underwater dataset for SLAM, object detection, and image segmentation. SubPipe has been recorded using a \gls{LAUV}, operated by OceanScan MST, and…
Loss it right: Euclidean and Riemannian Metrics in Learning-based Visual Odometry
Olaya Álvarez-Tuñón, Yury Brodskiy, Erdal Kayacan
This paper overviews different pose representations and metric functions in visual odometry (VO) networks. The performance of VO networks heavily relies on how their architecture e…
UNav-Sim: A Visually Realistic Underwater Robotics Simulator and Synthetic Data-generation Framework
Abdelhakim Amer, Olaya Álvarez-Tuñón, Halil Ibrahim Ugurlu +3
Underwater robotic surveys can be costly due to the complex working environment and the need for various sensor modalities. While underwater simulators are essential, many existing…
UnsuperPoint: End-to-end Unsupervised Interest Point Detector and Descriptor
Peter Hviid Christiansen, Mikkel Fly Kragh, Yury Brodskiy +1
It is hard to create consistent ground truth data for interest points in natural images, since interest points are hard to define clearly and consistently for a human annotator. Th…