LiDAR Technology for Autonomous Navigation and Mapping

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 spatial perception, environmental reconstruction, and SLAM, particularly in complex scenes such as dense urban areas, forests, and disaster-affected regions. 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 scene understanding and spatial modeling, laying the groundwork for subsequent tasks such as environmental monitoring, change detection, and hazard assessment.

This Special Issue aims to explore innovative research on the application of LiDAR technology in autonomous navigation and mapping, focusing on how LiDAR point clouds can be leveraged for spatial perception, environmental reconstruction, positioning, and mapping in typical scenarios. Topics may involve LiDAR-based methods or multi-sensor fusion solutions for understanding point cloud scenes and large-scale mapping in urban, natural, and disaster scenarios. The Special Issue topics include but are not limited to the following:

• LiDAR point cloud spatial perception and scene understanding;
• Autonomous navigation solutions (e.g., odometry, simultaneous localization and mapping);
• Mapping using LiDAR point clouds;
• LiDAR applications in GNSS-denied environments;
• LiDAR-based multi-sensor fusion systems;
• AI in LiDAR data processing.

Dr. Yiqing Yao
Prof. Dr. Johnson Ihyeh Agbinya
Guest Editors

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