73 citations · 93 across the 6 of their papers we have counts for
4 papers · 1 filter
Robust Monocular Localization in Sparse HD Maps Leveraging Multi-Task Uncertainty Estimation
Kürsat Petek, Kshitij Sirohi, Daniel Büscher +1
Robust localization in dense urban scenarios using a low-cost sensor setup and sparse HD maps is highly relevant for the current advances in autonomous driving, but remains a chall…
A Maximum Likelihood Approach to Extract Finite Planes from 3-D Laser Scans
Alexander Schaefer, Johan Vertens, Daniel Büscher +1
Whether it is object detection, model reconstruction, laser odometry, or point cloud registration: Plane extraction is a vital component of many robotic systems. In this paper, we…
A Maximum Likelihood Approach to Extract Polylines from 2-D Laser Range Scans
Alexander Schaefer, Daniel Büscher, Lukas Luft +1
Man-made environments such as households, offices, or factory floors are typically composed of linear structures. Accordingly, polylines are a natural way to accurately represent t…
Long-Term Urban Vehicle Localization Using Pole Landmarks Extracted from 3-D Lidar Scans
Alexander Schaefer, Daniel Büscher, Johan Vertens +2
Due to their ubiquity and long-term stability, pole-like objects are well suited to serve as landmarks for vehicle localization in urban environments. In this work, we present a co…