53 citations · 86 across the 12 of their papers we have counts for
5 papers · 1 filter
Oriented surface points for efficient and accurate radar odometry
Daniel Adolfsson, Martin Magnusson, Anas Alhashimi +2
This paper presents an efficient and accurate radar odometry pipeline for large-scale localization. We propose a radar filter that keeps only the strongest reflections per-azimuth…
CorAl -- Are the point clouds Correctly Aligned?
Daniel Adolfsson, Martin Magnusson, Qianfang Liao +2
In robotics perception, numerous tasks rely on point cloud registration. However, currently there is no method that can automatically detect misaligned point clouds reliably and wi…
BFAR-Bounded False Alarm Rate detector for improved radar odometry estimation
Anas Alhashimi, Daniel Adolfsson, Martin Magnusson +2
This paper presents a new detector for filtering noise from true detections in radar data, which improves the state of the art in radar odometry. Scanning Frequency-Modulated Conti…
CFEAR Radarodometry -- Conservative Filtering for Efficient and Accurate Radar Odometry
Daniel Adolfsson, Martin Magnusson, Anas Alhashimi +2
This paper presents the accurate, highly efficient, and learning-free method CFEAR Radarodometry for large-scale radar odometry estimation. By using a filtering technique that keep…
NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation
Zhicheng Zhou, Cheng Zhao, Daniel Adolfsson +4
3D point cloud-based place recognition is highly demanded by autonomous driving in GPS-challenged environments and serves as an essential component (i.e. loop-closure detection) in…