Learn how to design a lidar SLAM (Simultaneous Localization and Mapping) algorithm using synthetic lidar data recorded from a 3D environment. You can integrate with the photorealistic visualization capabilities from Unreal Engine^® by dragging and dropping out-of-the-box 3D Simulation blocks in Simulink. Discover how to visualize the recorded data, develop registration and mapping algorithms for perception, correct for drift using pose graph optimization, and achieve a cleaner and accurate point cloud map. Interested in lidar processing? Explore bat365' Lidar Toolbox for comprehensive lidar data analysis.

Key takeaways:

• How to design a lidar SLAM algorithm using synthetic lidar data
• Understand the process to integrate Simulink and Unreal Engine
• Discover techniques to visualize, process, and optimize lidar data for accurate mapping and localization.