Design Lidar-Based SLAM Using Unreal Engine Simulation Environment
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 MathWorks' 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.
Published: 11 Jan 2021
Featured Product
Automated Driving Toolbox
Up Next:
Related Videos:
Select a Web Site
Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .
You can also select a web site from the following list
How to Get Best Site Performance
Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites are not optimized for visits from your location.
Americas
- América Latina (Español)
- Canada (English)
- United States (English)
Europe
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)
Asia Pacific
- Australia (English)
- India (English)
- New Zealand (English)
- 中国
- 日本Japanese (日本語)
- 한국Korean (한국어)