KangchengLiu/DLC_LiDAR_SLAM

:fire: :muscle: Official Project: A Robust and Effective LiDAR-SLAM System with Learning-based Denoising and Loop Closure (DLC-SLAM)

41
/ 100
Emerging

This system helps autonomous robots, like drones and ground vehicles, navigate and build accurate maps in real-time, even in complex, noisy environments. It takes raw LiDAR and IMU sensor data, optionally enhanced with GPS, and outputs precise localization (the robot's position) and a detailed 3D map of its surroundings. Robotics engineers and researchers deploying robots in real-world scenarios would find this valuable.

150 stars. No commits in the last 6 months.

Use this if you need a robust, real-time Simultaneous Localization and Mapping (SLAM) solution for robotic platforms that primarily use LiDAR and IMU sensors in challenging outdoor or indoor conditions.

Not ideal if your application relies solely on visual sensors like cameras for navigation and mapping, as this system is optimized for LiDAR-based inputs.

robotics autonomous-navigation SLAM LiDAR-mapping drone-localization
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 15 / 25

How are scores calculated?

Stars

150

Forks

18

Language

C++

License

MIT

Last pushed

Dec 27, 2022

Commits (30d)

0

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