BALM 2.0

Efficient and Consistent Bundle Adjustment on Lidar Point Clouds

BALM 2.0 is a basic and simple system to use bundle adjustment (BA) in lidar mapping. It includes three experiments in the paper. We try to keep the code as concise as possible, to avoid confuse the readers. It is notable that this package do not include the application experiments, which will be open-sourced in other projects. The paper is available on Arxiv and more experiments details can be found in the video.

BALM: Bundle Adjustment for Lidar Mapping

1. Prerequisited

1.1 Ubuntu and ROS

Ubuntu 64-bit 20.04. ROS Installation. (Noetic recommended)

1.2 PCL and Eigen

Follow PCL Installation (1.10 recommended)

Follow Eigen Installation (3.3.7 recommended)

2. Build

Clone the repository and catkin_make:

cd ~/catkin_ws/src
git clone https://github.com/hku-mars/BALM
unzip balm2/datas
cd ../
catkin_make
source ~/catkin_ws/devel/setup.bash

3. Run the package

3.1 Consistency experiments

roslaunch balm2 consistency.launch

3.2 Benchmark on virtual point cloud

roslaunch balm2 benchmark_virtual.launch

3.3 Benchmark on real-world dataset

roslaunch balm2 benchmark_realworld.launch

Due to the file size, other dataset will be uploaded to one drive later.

4. Applications

Lidar-Inertial odometry with sliding window optimization: The codes will be open-sourced in the next work.
Multiple-Lidar calibration: More details can be seen here.
Global BA on large-scale dataset: More details can be seen here.

5. Acknowledgement

In the development of this package, we refer to FAST-LIO2, Hilti, VIRAL and UrbanLoco for source codes or datasets.

zaalsabb/BALM