48 citations · 50 across the 6 of their papers we have counts for
6 papers
SelfOccFlow: Towards end-to-end self-supervised 3D Occupancy Flow prediction
Xavier Timoneda, Markus Herb, Fabian Duerr +1
Estimating 3D occupancy and motion at the vehicle's surroundings is essential for autonomous driving, enabling situational awareness in dynamic environments. Existing approaches jo…
GroundLoc: Efficient Large-Scale Outdoor LiDAR-Only Localization
Nicolai Steinke, Daniel Goehring
In this letter, we introduce GroundLoc, a LiDAR-only localization pipeline designed to localize a mobile robot in large-scale outdoor environments using prior maps. GroundLoc emplo…
Impact of 3D LiDAR Resolution in Graph-based SLAM Approaches: A Comparative Study
J. Jorge, T. Barros, C. Premebida +3
Simultaneous Localization and Mapping (SLAM) is a key component of autonomous systems operating in environments that require a consistent map for reliable localization. SLAM has be…
MaskVal: Simple but Effective Uncertainty Quantification for 6D Pose Estimation
Philipp Quentin, Daniel Goehring
For the use of 6D pose estimation in robotic applications, reliable poses are of utmost importance to ensure a safe, reliable and predictable operational performance. Despite these…
GroundGrid:LiDAR Point Cloud Ground Segmentation and Terrain Estimation
Nicolai Steinke, Daniel Göhring, Raùl Rojas
The precise point cloud ground segmentation is a crucial prerequisite of virtually all perception tasks for LiDAR sensors in autonomous vehicles. Especially the clustering and extr…
Industrial Application of 6D Pose Estimation for Robotic Manipulation in Automotive Internal Logistics
Philipp Quentin, Dino Knoll, Daniel Goehring
Despite the advances in robotics a large proportion of the of parts handling tasks in the automotive industry's internal logistics are not automated but still performed by humans.…