23 citations · 25 across the 13 of their papers we have counts for
4 papers · 1 filter
A Low-Complexity Radar Detector Outperforming OS-CFAR for Indoor Drone Obstacle Avoidance
Ali Safa, Tim Verbelen, Lars Keuninckx +5
As radar sensors are being miniaturized, there is a growing interest for using them in indoor sensing applications such as indoor drone obstacle avoidance. In those novel scenarios…
Towards bio-inspired unsupervised representation learning for indoor aerial navigation
Ni Wang, Ozan Catal, Tim Verbelen +2
Aerial navigation in GPS-denied, indoor environments, is still an open challenge. Drones can perceive the environment from a richer set of viewpoints, while having more stringent c…
LatentSLAM: unsupervised multi-sensor representation learning for localization and mapping
Ozan Çatal, Wouter Jansen, Tim Verbelen +2
Biologically inspired algorithms for simultaneous localization and mapping (SLAM) such as RatSLAM have been shown to yield effective and robust robot navigation in both indoor and…
Learning to Catch Piglets in Flight
Ozan Çatal, Lawrence De Mol, Tim Verbelen +1
Catching objects in-flight is an outstanding challenge in robotics. In this paper, we present a closed-loop control system fusing data from two sensor modalities: an RGB-D camera a…