LiDAR Technology for Autonomous Navigation and Mapping
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".
Deadline for manuscript submissions: 28 August 2025 | Viewed by 137
Special Issue Editors
Interests: LiDAR; inertial navigation; integration systems; multi-sensor data fusion scheme; polar navigation
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; sensors; smart environments; deep learning; IoT; radar (LiDAR); wireless power transfer
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Autonomous navigation and mapping has always been a prerequisite and essential foundation for autonomous systems, providing location and environmental information for decision making and vehicle operation. In recent years, LiDAR systems have demonstrated tremendous potential for enhancing perception capabilities in autonomous navigation and mapping tasks. Autonomous vehicles, ships, and drones, for instance, rely heavily on LiDAR for safe and efficient navigation, particularly in GNSS-denied and challenged environments such as indoors, underground, and in urban canyon areas. Quantities of corresponding algorithms and methodologies are proposed, which may rely solely on LiDAR or integrate data from multiple sources (e.g., inertial measurement units, cameras, or radars). Furthermore, due to LiDAR’s high ranging accuracy and its ability to provide detailed point cloud data, it offers significant advantages for mapping and environmental perception, laying the groundwork for subsequent tasks such as path planning and mission execution.
This Special Issue aims to explore innovative research on the application of LiDAR technology in autonomous navigation and mapping. Topics may involve positioning, detection, or mapping using LiDAR-based methods or multi-sensor fusion solutions in various environments, including indoors and in urban settings. The Special Issue topics include but are not limited to the following:
Autonomous navigation solutions (e.g., odometry, simultaneous localization and mapping);
Autonomous detection and avoidance (e.g., for targets or obstacles);
Mapping using LiDAR point clouds;
LiDAR applications in GNSS-denied environments;
LiDAR-based multi-sensor fusion systems;
AI in LiDAR data processing;
Autonomous decision-making models using LiDAR.
Dr. Yiqing Yao
Prof. Dr. Johnson Ihyeh Agbinya
Guest Editors
Manuscript Submission Information
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Keywords
- LiDAR odometry
- simultaneous localization and mapping
- obstacle detection and avoidance
- 3D mapping
- multi-sensor fusion
- autonomous vehicles
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