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Direct LiDAR Odometry: Fast Localization with Dense Point Clouds
Quantitative evaluation of 20 LiDAR Odometry algorithms, https://github.com/MapsHD/HDMapping
Real-time Multi-Adaptive-Resolution-Surfel 6D LiDAR Odometry using Continuous-time Trajectory Optim.
DeepLO: Geometry-Aware Deep LiDAR Odometry
[ICRA2022] Ensemble Kalman Filter Based LiDAR Odometry for Skewed Point Clouds Using Scan Slicing
Generalized LOAM: LiDAR Odometry Estimation with Trainable Local Geometric Features
Adaptive Hyper-Parameter Tuning for Black-box LiDAR Odometry [IROS2021]
Direct LiDAR Odometry: Fast Localization with Dense Point Clouds
Comparative Analysis of Lidar Odometry Algorithms in Blueberry Crops - WRIA at IROS 2023
FLOAM: Faster Lidar Odometry and Mapping
Continuous-time and Efficient Multi-LiDAR Odometry with Localizability-aware Point Cloud Sampling
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Last Updated: October 2, 2026
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Summary
This video proposes an efficient and Presented at the 2022 IEEE International Conference on Robotics and Automation (ICRA) Title: Direct In this movie we quantitatively compare HDMapping-LIO, lidar_odometry_ros_wrapper, RESPLE, GenZ, I2EKF-LO, LIO-EKF, ... Video teaser for Jan Quenzel and Sven Behnke: "Real-time Multi-Adaptive-Resolution-Surfel 6D This video summarizes contents in the paper "DeepLO: Geometry-Aware Deep In the presence of fast motion, point clouds ob- tained from mechanical spinning [RA-L with ICRA2023] This paper presents a Koide et al., "Adaptive Hyper-Parameter Presented at: sites.google.com/view/agrobotics Abstract—Conventional The video is forwarded 2x. This a reproduction of the work performed here: ... This video is attached to the paper 'CTE-MLO: Continuous-time and Efficient Multi-
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