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   Articles with "lidar odometry" as a keyword



SLOAM: Semantic Lidar Odometry and Mapping for Forest Inventory

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recommendations! 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

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recommendations! 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

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recommendations! 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

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recommendations! 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

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recommendations! 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

MAD-ICP: It is All About Matching Data – Robust and Informed LiDAR Odometry

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recommendations! Published in 2024 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2024.3456509

Abstract: LiDAR odometry is the task of estimating the ego-motion of the sensor from sequential laser scans. This problem has been addressed by the community for more than two decades, and many effective solutions are available… read more here.

Keywords: odometry; icp matching; mad icp; lidar odometry ... See more keywords

GenZ-ICP: Generalizable and Degeneracy-Robust LiDAR Odometry Using an Adaptive Weighting

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recommendations! Published in 2024 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2024.3498779

Abstract: Light detection and ranging (LiDAR)-based odometry has been widely utilized for pose estimation due to its use of high-accuracy range measurements and immunity to ambient light conditions. However, the performance of LiDAR odometry varies depending… read more here.

Keywords: lidar; point; genz icp; lidar odometry ... See more keywords

DBSCAN-Based Dynamic Object Recognition and Semantic Information Entropy-Assisted Vehicle LiDAR Odometry

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recommendations! Published in 2025 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2025.3571084

Abstract: In vehicle LiDAR odometry, a common challenge arises from the feature misalignment caused by dynamic objects. Although current popular deep-learning-based semantic segmentation methods are able to effectively identify dynamic objects, they are limited to recognizing… read more here.

Keywords: odometry; lidar odometry; semantic information; dynamic objects ... See more keywords

An Adaptive ICP LiDAR Odometry Based on Reliable Initial Pose

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recommendations! Published in 2025 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2025.3571148

Abstract: As a key technology for autonomous navigation and positioning in mobile robots, light detection and ranging (LiDAR) odometry is widely used in autonomous driving applications. The iterative closest point (ICP)-based methods have become the core… read more here.

Keywords: initial pose; adaptive icp; point; lidar odometry ... See more keywords

Self-Supervised Depth Completion From Direct Visual-LiDAR Odometry in Autonomous Driving

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recommendations! 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.

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recommendations! 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