513 citations · 812 across the 8 of their papers we have counts for
8 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…
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…
KISS-Matcher: Fast and Robust Point Cloud Registration Revisited
Hyungtae Lim, Daebeom Kim, Gunhee Shin +5
While global point cloud registration systems have advanced significantly in all aspects, many studies have focused on specific components, such as feature extraction, graph-theore…
Building Volumetric Beliefs for Dynamic Environments Exploiting Map-Based Moving Object Segmentation
Benedikt Mersch, Tiziano Guadagnino, Xieyuanli Chen +3
Mobile robots that navigate in unknown environments need to be constantly aware of the dynamic objects in their surroundings for mapping, localization, and planning. It is key to r…
KISS-ICP: In Defense of Point-to-Point ICP -- Simple, Accurate, and Robust Registration If Done the Right Way
Ignacio Vizzo, Tiziano Guadagnino, Benedikt Mersch +3
Robust and accurate pose estimation of a robotic platform, so-called sensor-based odometry, is an essential part of many robotic applications. While many sensor odometry systems ma…
Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions
Benedikt Mersch, Xieyuanli Chen, Ignacio Vizzo +3
A key challenge for autonomous vehicles is to navigate in unseen dynamic environments. Separating moving objects from static ones is essential for navigation, pose estimation, and…
Automatic Labeling to Generate Training Data for Online LiDAR-based Moving Object Segmentation
Xieyuanli Chen, Benedikt Mersch, Lucas Nunes +4
Understanding the scene is key for autonomously navigating vehicles and the ability to segment the surroundings online into moving and non-moving objects is a central ingredient fo…
Range Image-based LiDAR Localization for Autonomous Vehicles
Xieyuanli Chen, Ignacio Vizzo, Thomas Läbe +2
Robust and accurate, map-based localization is crucial for autonomous mobile systems. In this paper, we exploit range images generated from 3D LiDAR scans to address the problem of…