SLOAM: Semantic Lidar Odometry and Mapping for Forest Inventory
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2019.2963823
Abstract: This letter describes an end-to-end pipeline for tree diameter estimation based on semantic segmentation and lidar odometry and mapping. Accurate mapping of this type of environment is challenging since the ground and the trees are… read more here.
Keywords: lidar odometry; lidar; sloam semantic; odometry mapping ... See more keywords
FasterGICP: Acceptance-Rejection Sampling Based 3D Lidar Odometry
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2021.3124072
Abstract: Distribution-to-distribution-based lidar odometry is known for its good accuracy, while it cannot run in real-time when the number of points is large. To alleviate this problem, Faster Generalized Iterative Closest Point (FasterGICP) is proposed in… read more here.
Keywords: acceptance rejection; rejection sampling; lidar odometry; odometry ... See more keywords
Robust Self-Supervised LiDAR Odometry Via Representative Structure Discovery and 3D Inherent Error Modeling
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3140794
Abstract: The correct ego-motion estimation basically relies on the understanding of correspondences between adjacent LiDAR scans. However, given the complex scenarios and the low-resolution LiDAR, finding reliable structures for identifying correspondences can be challenging. In this… read more here.
Keywords: odometry; lidar odometry; self supervised; ego motion ... See more keywords
Direct LiDAR Odometry: Fast Localization With Dense Point Clouds
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3142739
Abstract: Field robotics in perceptually-challenging environments require fast and accurate state estimation, but modern LiDAR sensors quickly overwhelm current odometry algorithms. To this end, this letter presents a lightweight frontend LiDAR odometry solution with consistent and… read more here.
Keywords: point; point clouds; direct lidar; lidar odometry ... See more keywords
FEVO-LOAM: Feature Extraction and Vertical Optimized Lidar Odometry and Mapping
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2022.3201689
Abstract: Simultaneous Localization and Mapping (SLAM) is a significant research topic in robotics since it is one of the key technologies for robot automation. Although lidar-based SLAM methods have achieved promising performance, traditional lidar SLAM methods… read more here.
Keywords: extraction vertical; lidar odometry; optimized lidar; extraction ... See more keywords
Self-Supervised Depth Completion From Direct Visual-LiDAR Odometry in Autonomous Driving
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3106055
Abstract: In this work, a simple yet effective deep neural network is proposed to generate the dense depth map of the scene by exploiting both LiDAR sparse point cloud and the monocular camera image. Specifically, a… read more here.
Keywords: network; completion; lidar odometry; depth completion ... See more keywords
SDV-LOAM: Semi-Direct Visual-LiDAR Odometry and Mapping.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2023.3262817
Abstract: Visual-LiDAR odometry and mapping (V-LOAM), which fuses complementary information of a camera and a LiDAR, is an attractive solution for accurate and robust pose estimation and mapping. However, existing systems could suffer nontrivial tracking errors… read more here.
Keywords: sdv loam; odometry; lidar odometry; lidar ... See more keywords
A Hierarchical LiDAR Odometry via Maximum Likelihood Estimation With Tightly Associated Distributions
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2022.3183202
Abstract: LiDAR odometry has gained popularity due to accurate depth measurement with the robustness to illuminations. However, existing distribution-based methods do not sufficiently exploit the information from source point cloud, which affects the odometry performance. In… read more here.
Keywords: lidar odometry; hierarchical lidar; likelihood estimation; maximum likelihood ... See more keywords
A 3D LiDAR odometry for UGVs using coarse-to-fine deep scene flow estimation
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DOI: 10.1177/01423312221105165
Abstract: Light detection and ranging (LiDAR) odometry plays a crucial role in autonomous mobile robots and unmanned ground vehicles (UGVs). This paper presents a deep learning–based odometry system using two successive three-dimensional (3D) point clouds to… read more here.
Keywords: coarse fine; scene flow; odometry; lidar odometry ... See more keywords
Self-supervised learning of LiDAR odometry based on spherical projection
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Advanced Robotic Systems"
DOI: 10.1177/17298806221078669
Abstract: Recently, the learning-based LiDAR odometry has obtained robust estimation results in the field of mobile robot localization, but most of them are constructed based on the idea of supervised learning. In the network training stage,… read more here.
Keywords: point; supervised learning; projection; lidar odometry ... See more keywords