IS-CAT: Intensity–Spatial Cross-Attention Transformer for LiDAR-Based Place Recognition
LiDAR place recognition is a crucial component of autonomous navigation, essential for loop closure in simultaneous localization and mapping (SLAM) systems. Notably, while camera-based methods struggle in fluctuating environments, such as weather or light, LiDAR demonstrates robustness against such...
Main Authors: | Hyeong-Jun Joo, Jaeho Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-01-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/24/2/582 |
Similar Items
-
The New Method of Active SLAM for Mapping Using LiDAR
by: Michal Mihálik, et al.
Published: (2022-03-01) -
Enhancing Solid State LiDAR Mapping with a 2D Spinning LiDAR in Urban Scenario SLAM on Ground Vehicles
by: Weichen Wei, et al.
Published: (2021-03-01) -
ZUST Campus: A Lightweight and Practical LiDAR SLAM Dataset for Autonomous Driving Scenarios
by: Yuhang He, et al.
Published: (2024-04-01) -
A Benchmark for Multi-Modal LiDAR SLAM with Ground Truth in GNSS-Denied Environments
by: Ha Sier, et al.
Published: (2023-06-01) -
RSS-LIWOM: Rotating Solid-State LiDAR for Robust LiDAR-Inertial-Wheel Odometry and Mapping
by: Shunjie Gong, et al.
Published: (2023-08-01)