This work is an optimized version of A-LOAM and LOAM with the computational cost reduced by up to 3 times. This code is modified from LOAM and A-LOAM .
Modifier: Wang Han, Nanyang Technological University, Singapore
ROS2 Migration: Yi-Chen Zhang, Isuzu Technical Center of America, USA
Watch our demo at Video Link
Computational efficiency evaluation (based on KITTI dataset): Platform: Intel® Core™ i7-8700 CPU @ 3.20GHz
Dataset | ALOAM | FLOAM |
---|---|---|
KITTI |
151ms | 59ms |
Localization error:
Dataset | ALOAM | FLOAM |
---|---|---|
KITTI sequence 00 |
0.55% | 0.51% |
KITTI sequence 02 |
3.93% | 1.25% |
KITTI sequence 05 |
1.28% | 0.93% |
Ubuntu 64-bit 20.04.
ROS2 Foxy. ROS Installation
Follow Ceres Installation. Please checkout to 2.0.0 tag. ROS2 migrated version doest not support Ceres 2.1.0 yet.
For PCL library, please install by the following:
sudo apt-get install libpcl-dev ros-foxy-pcl-ros
cd ~/colcon_ws/src
git clone https://github.com/chris7462/floam.git
cd ..
colcon build
source ./install/setup.bash
Download KITTI sequence 05 or KITTI sequence 07
Unzip compressed file 2011_09_30_0018.zip. If your system does not have unzip. please install unzip by
sudo apt-get install unzip
And this may take a few minutes to unzip the file
cd ~/Downloads
unzip ~/Downloads/2011_09_30_0018.zip
Then convert the ROS1 bag to ROS2 bag. See here for reference
ros2 launch floam floam.launch.py
if you would like to create the map at the same time, you can run (more cpu cost)
ros2 launch floam floam_mapping.launch.py
If the mapping process is slow, you may wish to change the rosbag speed by replacing "-r 0.5" with "-r 0.2" in your launch file, or you can change the map publish frequency manually (default is 10 Hz)
To generate rosbag file of kitti dataset, you may use the tools provided by kitti_to_rosbag or kitti2bag
Thanks for A-LOAM and LOAM (J. Zhang and S. Singh. LOAM: Lidar Odometry and Mapping in Real-time) and LOAM_NOTED.
If you use this work for your research, you may want to cite
@inproceedings{wang2021,
author={H. {Wang} and C. {Wang} and C. {Chen} and L. {Xie}},
booktitle={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
title={F-LOAM : Fast LiDAR Odometry and Mapping},
year={2020},
volume={},
number={}
}