The official implementation of the paper "Fast LiDAR-Inertial Odometry via Incremental Plane Pre-Fitting and Skeleton Tracking" (IROS 2023)
We introduce LIO-PPF, a plane pre-fitting and skeleton tracking technique, that can ease the computation of state-of-the-art LIO systems, e.g. LIO-SAM. Please refer to this
In LIO-PPF, we track mainly the basic skeleton of the 3D scene, the planes of which are not fitted individually for each LiDAR scan, let alone for each LiDAR point. However, they are updated incrementally as the scene gradually `flows'.
By contrast, LIO-PPF can consume only 36% of the original local map size to achieve up to 4x faster residual computing and 1.92x overall FPS, while maintaining the same level of accuracy.
catkin_make
source devel/setup.bash
roslaunch lio_sam run.launch
In another terminal:
rosbag play /path/to/your/bag/file
For details about building and running, please refer to LIO-SAM.
If you are looking for FasterLIO with PPF, please check out faster-lio-ppf.
If you find our work useful or interesting, please consider citing our paper:
@inproceedings{chen2023lio,
title={LIO-PPF: Fast LiDAR-Inertial Odometry via Incremental Plane Pre-Fitting and Skeleton Tracking},
author={Chen, Xingyu and
Wu, Peixi and
Li, Ge and
Li, Thomas H},
booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages={1458--1465},
year={2023},
organization={IEEE}
}