Neural network-based recent research developments in SLAM for autonomous ground vehicles: A review

H Saleem, R Malekian, H Munir - IEEE Sensors Journal, 2023 - ieeexplore.ieee.org
The development of autonomous vehicles has prompted an interest in exploring various
techniques in navigation. One such technique is simultaneous localization and map** …

LiDAR odometry survey: recent advancements and remaining challenges

D Lee, M Jung, W Yang, A Kim - Intelligent Service Robotics, 2024 - Springer
Odometry is crucial for robot navigation, particularly in situations where global positioning
methods like global positioning system are unavailable. The main goal of odometry is to …

MULLS: Versatile LiDAR SLAM via multi-metric linear least square

Y Pan, P ** calls for off-the-shelf
LiDAR SLAM solutions that are adaptive to LiDARs of different specifications on various …

Translo: A window-based masked point transformer framework for large-scale lidar odometry

J Liu, G Wang, C Jiang, Z Liu, H Wang - Proceedings of the AAAI …, 2023 - ojs.aaai.org
Recently, transformer architecture has gained great success in the computer vision
community, such as image classification, object detection, etc. Nonetheless, its application …

Pwclo-net: Deep lidar odometry in 3d point clouds using hierarchical embedding mask optimization

G Wang, X Wu, Z Liu, H Wang - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
A novel 3D point cloud learning model for deep LiDAR odometry, named PWCLO-Net, using
hierarchical embedding mask optimization is proposed in this paper. In this model, the …

Efficient 3d deep lidar odometry

G Wang, X Wu, S Jiang, Z Liu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
An efficient 3D point cloud learning architecture, named EfficientLO-Net, for LiDAR odometry
is first proposed in this article. In this architecture, the projection-aware representation of the …

A practical survey on visual odometry for autonomous driving in challenging scenarios and conditions

LR Agostinho, NM Ricardo, MI Pereira, A Hiolle… - IEEE …, 2022 - ieeexplore.ieee.org
The expansion of autonomous driving operations requires the research and development of
accurate and reliable self-localization approaches. These include visual odometry methods …

4DRVO-Net: Deep 4D radar–visual odometry using multi-modal and multi-scale adaptive fusion

G Zhuo, S Lu, H Zhou, L Zheng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Four-dimensional (4D) radar–visual odometry (4DRVO) integrates complementary
information from 4D radar and cameras, making it an attractive solution for achieving …

Efficient deep-learning 4d automotive radar odometry method

S Lu, G Zhuo, L **ong, X Zhu, L Zheng… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Odometry is a crucial technology for the autonomous positioning of intelligent vehicles.
While estimating the odometry from LiDAR and cameras has progressed recently, it remains …

SLAMICP library: Accelerating obstacle detection in mobile robot navigation via outlier monitoring following icp localization

E Clotet, J Palacín - Sensors, 2023 - mdpi.com
The Iterative Closest Point (ICP) is a matching technique used to determine the
transformation matrix that best minimizes the distance between two point clouds. Although …