lio-mapping

Simultaneously optimizes LiDAR and IMU measurements within a unified framework, leading to improved accuracy and robustness in feature-poor environments, as evidenced by the ICRA 2019 paper and demo results.

Processes sensor data on-the-fly to provide immediate pose estimation and map updates, making it suitable for autonomous navigation tasks in dynamic settings.

Built as a ROS package with launch files, enabling easy integration into existing robotic systems and toolchains, as shown in the build and example instructions.

Includes Dockerfiles and scripts for containerized setup with GPU-accelerated visualization options, simplifying deployment and reproducibility across different environments.