Publications (16)
DMSA -- Dense Multi Scan Adjustment for LiDAR Inertial Odometry and Global Optimization
David Skuddis, Norbert Haala
We propose a new method for fine registering multiple point clouds simultaneously. The approach is characterized by being dense, therefore point clouds are not reduced to pre-selec…
SLAM for Indoor Mapping of Wide Area Construction Environments
Vincent Ress, Wei Zhang, David Skuddis +2
Simultaneous localization and mapping (SLAM), i.e., the reconstruction of the environment represented by a (3D) map and the concurrent pose estimation, has made astonishing progres…
Photometric Multi-View Mesh Refinement for High-Resolution Satellite Images
Mathias Rothermel, Ke Gong, Dieter Fritsch +2
Modern high-resolution satellite sensors collect optical imagery with ground sampling distances (GSDs) of 30-50cm, which has sparked a renewed interest in photogrammetric 3D surfac…
BEV-SLD: Self-Supervised Scene Landmark Detection for Global Localization with LiDAR Bird's-Eye View Images
David Skuddis, Vincent Ress, Wei Zhang +2
We present BEV-SLD, a LiDAR global localization method building on the Scene Landmark Detection (SLD) concept. Unlike scene-agnostic pipelines, our self-supervised approach leverag…
An RTK-SLAM Dataset for Absolute Accuracy Evaluation in GNSS-Degraded Environments
Wei Zhang, Vincent Ress, David Skuddis +2
RTK-SLAM systems integrate simultaneous localization and mapping (SLAM) with real-time kinematic (RTK) GNSS positioning, promising both relative consistency and globally referenced…
Accuracy potential of visual localization exploiting high-end street-level imagery
Jonas Meyer, Stephan Nebiker, Pascal Theiler +1
Accurate and reliable pose information with respect to a reference frame is increasingly demanded across applications such as autonomous navigation, surveying, robotics, and augmen…