Lightweight 3-D Localization and Mapping for Solid-State LiDAR

@article{Wang2021Lightweight3L,
  title={Lightweight 3-D Localization and Mapping for Solid-State LiDAR},
  author={Han Wang and Chen Wang and Lihua Xie},
  journal={IEEE Robotics and Automation Letters},
  year={2021},
  volume={6},
  pages={1801-1807}
}
The LIght Detection And Ranging (LiDAR) sensor has become one of the most important perceptual devices due to its important role in simultaneous localization and mapping (SLAM). Existing SLAM methods are mainly developed for mechanical LiDAR sensors, which are often adopted by large scale robots. Recently, the solid-state LiDAR is introduced and becomes popular since it provides a cost-effective and lightweight solution for small scale robots. Compared to mechanical LiDAR, solid-state LiDAR… 

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References

SHOWING 1-10 OF 28 REFERENCES
Tightly Coupled 3D Lidar Inertial Odometry and Mapping
TLDR
The proposed tightly coupled lidar-IMU fusion method can estimate the poses of the sensor pair at the IMU update rate with high precision, even under fast motion conditions or with insufficient features.
LOL: Lidar-only Odometry and Localization in 3D point cloud maps*
TLDR
This paper integrates a state-of-the-art Lidaronly odometry algorithm with a recently proposed 3D point segment matching method by complementing their advantages and demonstrates the utility of the proposed LOL system on several Kitti datasets of different lengths and environments.
IMLS-SLAM: Scan-to-Model Matching Based on 3D Data
  • Jean-Emmanuel Deschaud
  • Environmental Science
    2018 IEEE International Conference on Robotics and Automation (ICRA)
  • 2018
TLDR
This work presents a new low-drift SLAM algorithm based only on 3D LiDAR data that relies on a scan-to-model matching framework and uses the Implicit Moving Least Squares (IMLS) surface representation.
LOAM: Lidar Odometry and Mapping in Real-time
TLDR
The method achieves both low-drift and low-computational complexity without the need for high accuracy ranging or inertial measurements and can achieve accuracy at the level of state of the art offline batch methods.
Loam livox: A fast, robust, high-precision LiDAR odometry and mapping package for LiDARs of small FoV
  • Jiarong Lin, Fu Zhang
  • Environmental Science
    2020 IEEE International Conference on Robotics and Automation (ICRA)
  • 2020
TLDR
This paper presents a robust, real-time LOAM algorithm for LiDARs with small FoV and irregular samplings, and addresses several fundamental challenges arising from such LiDars, and achieves better performance in both precision and efficiency compared to existing baselines.
Visual-lidar odometry and mapping: low-drift, robust, and fast
  • Ji Zhang, Sanjiv Singh
  • Environmental Science
    2015 IEEE International Conference on Robotics and Automation (ICRA)
  • 2015
Here, we present a general framework for combining visual odometry and lidar odometry in a fundamental and first principle method. The method shows improvements in performance over the state of the
Development of a UAV-LiDAR System with Application to Forest Inventory
TLDR
The development of a low-cost UAV-LiDAR system and an accompanying workflow to produce 3D point clouds and a novel trajectory determination algorithm fusing observations from a GPS receiver, an Inertial Measurement Unit and a High Definition (HD) video camera are presented.
LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping
We propose a framework for tightly-coupled lidar inertial odometry via smoothing and mapping, LIO-SAM, that achieves highly accurate, real-time mobile robot trajectory estimation and map-building.
A portable three-dimensional LIDAR-based system for long-term and wide-area people behavior measurement
TLDR
A portable people behavior measurement system using a three-dimensional LIDAR that enables long-term and wide-area people behavior measurements which are hard for existing people tracking systems.
LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain
  • Tixiao Shan, Brendan Englot
  • Computer Science
    2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • 2018
TLDR
A lightweight and ground-optimized lidar odometry and mapping method, LeGO-LOAM, for realtime six degree-of-freedom pose estimation with ground vehicles and integrated into a SLAM framework to eliminate the pose estimation error caused by drift is integrated.
...
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