. Discusses in detail LiDAR's working principles, laser pulse wavelengths, point cloud data, motion compensation, and datasets commonly used in LiDAR research.
. Examines the effects of ambient light, adverse weather conditions (rain, fog, snow), and practical strategies for mitigating these challenges.
. Describes advanced methods for object detection, segmentation, and multi-object tracking using LiDAR point clouds, including solutions like AnchorPoint and Smart3DMOT.
. Presents techniques for creating high-definition 3D maps and implementing SLAM (Simultaneous Localization and Mapping) that are essential for autonomous navigation.
. Offers practical insights into autonomous navigation, including LiDAR-based localization, path planning, obstacle avoidance, and real-world case studies like autonomous shuttles.
. Explores multi-LiDAR calibration, emphasizing alignment, fusion, and synchronization to enhance coverage and reduce blind spots in autonomous systems.
· Offers a detailed guide on open-source LiDAR processing tools like PCL, Open3D, and ROS for data handling and visualization.
By combining theoretical principles with practical applications and case studies, this book serves as a reference book for academics and researchers in computer science, electronics, communication engineering, and autonomous technologies.
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