3 citations · 4 across the 4 of their papers we have counts for
6 papers
Neural Surface and Reflectance Modelling from 3D Radar Data
Judith Treffler, VladimÃr Kubelka, Henrik Andreasson +1
Robust scene representation is essential for autonomous systems to safely operate in challenging low-visibility environments. In these conditions, radar has a clear advantage over…
Viking Hill Dataset: A Lidar-Radar-Camera Dataset for Detection and Segmentation in Forest Scenes
VladimÃr Kubelka, Oleksandr Kotlyar, Unal Artan +1
Autonomous robots operating under forest canopies need robust perception of trees and surrounding vegetation across varying seasonal conditions. Existing forestry datasets provide…
Lidar Scan Registration Robust to Extreme Motions
Simon-Pierre Deschênes, Dominic Baril, VladimÃr Kubelka +2
Registration algorithms, such as Iterative Closest Point (ICP), have proven effective in mobile robot localization algorithms over the last decades. However, they are susceptible t…
4D Radar Semantic Segmentation of People in Field Conditions Using Temporal Multi-View Networks
Mikael Skog, Oleksandr Kotlyar, VladimÃr Kubelka +1
Reliable people detection is crucial for the safe autonomy of mobile robots and heavy vehicles, both on roads and in industrial settings like mining and construction. However, comm…
MonoForce: Self-supervised Learning of Physics-informed Model for Predicting Robot-terrain Interaction
Ruslan Agishev, Karel Zimmermann, VladimÃr Kubelka +2
While autonomous navigation of mobile robots on rigid terrain is a well-explored problem, navigating on deformable terrain such as tall grass or bushes remains a challenge. To addr…
Introspective Loop Closure for SLAM with 4D Imaging Radar
Maximilian Hilger, VladimÃr Kubelka, Daniel Adolfsson +3
Simultaneous Localization and Mapping (SLAM) allows mobile robots to navigate without external positioning systems or pre-existing maps. Radar is emerging as a valuable sensing too…