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20232026
most citedGroundGrid:LiDAR Point Cloud Ground Segmentation and Terrain Estimation

48 citations · 50 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.RO2025★ 2 cited

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…

cs.RO2024

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…

cs.RO2024

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…

cs.RO2024★ 48 cited

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…

cs.RO2023

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.…