A-LOAM
A clean, simplified implementation of the LOAM algorithm for real-time LiDAR odometry and mapping using Eigen and Ceres Solver.
What is A-LOAM?
A-LOAM is an open-source implementation of the LOAM algorithm for real-time LiDAR odometry and mapping. It processes 3D point cloud data from LiDAR sensors to simultaneously localize a robot and build a map of its environment. The project simplifies the original LOAM codebase using Eigen and Ceres Solver libraries, making it more accessible for educational purposes.
Robotics researchers, autonomous vehicle developers, and students learning SLAM algorithms who need a clean, understandable implementation of real-time LiDAR odometry and mapping.
Developers choose A-LOAM because it provides a production-ready implementation of LOAM with significantly simplified code structure, making it easier to understand, modify, and extend compared to the original algorithm while maintaining real-time performance.
Overview
Advanced implementation of LOAM
Use Cases
Best For
- Learning SLAM algorithms through clean, well-structured code
- Real-time LiDAR odometry for autonomous robots and drones
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
