1 citations · 3 across the 5 of their papers we have counts for
5 papers
KISS-SLAM: A Simple, Robust, and Accurate 3D LiDAR SLAM System With Enhanced Generalization Capabilities
Tiziano Guadagnino, Benedikt Mersch, Saurabh Gupta +3
Robust and accurate localization and mapping of an environment using laser scanners, so-called LiDAR SLAM, is essential to many robotic applications. Early 3D LiDAR SLAM methods of…
Efficiently Closing Loops in LiDAR-Based SLAM Using Point Cloud Density Maps
Saurabh Gupta, Tiziano Guadagnino, Benedikt Mersch +3
Consistent maps are key for most autonomous mobile robots, and they often use SLAM approaches to build such maps. Loop closures via place recognition help to maintain accurate pose…
Kinematic-ICP: Enhancing LiDAR Odometry with Kinematic Constraints for Wheeled Mobile Robots Moving on Planar Surfaces
Tiziano Guadagnino, Benedikt Mersch, Ignacio Vizzo +5
LiDAR odometry is essential for many robotics applications, including 3D mapping, navigation, and simultaneous localization and mapping. LiDAR odometry systems are usually based on…
HeLiMOS: A Dataset for Moving Object Segmentation in 3D Point Clouds From Heterogeneous LiDAR Sensors
Hyungtae Lim, Seoyeon Jang, Benedikt Mersch +3
Moving object segmentation (MOS) using a 3D light detection and ranging (LiDAR) sensor is crucial for scene understanding and identification of moving objects. Despite the availabi…
Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion
Lucas Nunes, Rodrigo Marcuzzi, Benedikt Mersch +2
Computer vision techniques play a central role in the perception stack of autonomous vehicles. Such methods are employed to perceive the vehicle surroundings given sensor data. 3D…