A survey on ground segmentation methods for automotive LiDAR sensors

T Gomes, D Matias, A Campos, L Cunha, R Roriz - Sensors, 2023 - mdpi.com
In the near future, autonomous vehicles with full self-driving features will populate our public
roads. However, fully autonomous cars will require robust perception systems to safely …

Nerf-loam: Neural implicit representation for large-scale incremental lidar odometry and mapping

J Deng, Q Wu, X Chen, S Xia, Z Sun… - Proceedings of the …, 2023 - openaccess.thecvf.com
Simultaneously odometry and mapping using LiDAR data is an important task for mobile
systems to achieve full autonomy in large-scale environments. However, most existing …

Patchwork++: Fast and robust ground segmentation solving partial under-segmentation using 3d point cloud

S Lee, H Lim, H Myung - 2022 IEEE/RSJ International …, 2022 - ieeexplore.ieee.org
In the field of 3D perception using 3D LiDAR sensors, ground segmentation is an essential
task for various purposes, such as traversable area detection and object recognition. Under …

DreamWaQ: Learning robust quadrupedal locomotion with implicit terrain imagination via deep reinforcement learning

IMA Nahrendra, B Yu, H Myung - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
Quadrupedal robots resemble the physical ability of legged animals to walk through
unstructured terrains. However, designing a controller for quadrupedal robots poses a …

Quatro++: Robust global registration exploiting ground segmentation for loop closing in LiDAR SLAM

H Lim, B Kim, D Kim, E Mason Lee… - … International Journal of …, 2024 - journals.sagepub.com
Global registration is a fundamental task that estimates the relative pose between two
viewpoints of 3D point clouds. However, there are two issues that degrade the performance …

Robust multi-task learning network for complex LiDAR point cloud data preprocessing

L Zhao, Y Hu, X Yang, Z Dou, L Kang - Expert Systems with Applications, 2024 - Elsevier
The utilization of 3D point clouds acquired via Light Detection and Ranging (LiDAR) is
widespread in the fields of autonomous driving, satellite remote sensing, and spatial …

A single correspondence is enough: Robust global registration to avoid degeneracy in urban environments

H Lim, S Yeon, S Ryu, Y Lee, Y Kim… - … on robotics and …, 2022 - ieeexplore.ieee.org
Global registration using 3D point clouds is a crucial technology for mobile platforms to
achieve localization or manage loop-closing situations. In recent years, numerous …

Static map generation from 3D LiDAR point clouds exploiting ground segmentation

M Arora, L Wiesmann, X Chen, C Stachniss - Robotics and Autonomous …, 2023 - Elsevier
A clean and reliable map of the environment is key for a variety of robotic tasks including
localization, path planning, and navigation. Dynamic objects are an inherent part of our …

AdaLIO: Robust adaptive LiDAR-inertial odometry in degenerate indoor environments

H Lim, D Kim, B Kim, H Myung - 2023 20th International …, 2023 - ieeexplore.ieee.org
In recent years, the demand for mapping construction sites or buildings using light detection
and ranging (LiDAR) sensors has been increased to model environments for efficient site …

Bevcontrast: Self-supervision in bev space for automotive lidar point clouds

C Sautier, G Puy, A Boulch, R Marlet… - … Conference on 3D …, 2024 - ieeexplore.ieee.org
We present a surprisingly simple and efficient method for self-supervision of 3D backbone
on automotive Lidar point clouds. We design a contrastive loss between features of Lidar …