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C3P-VoxelMap

This repository implements C3P-VoxelMap, a compact, cumulative, and coalescible probabilistic voxel mapping method to enhance performance, accuracy, and memory efficiency in LiDAR odometry. Based on VoxelMap, our work reduces memory consumption by two strategies:

  1. Compact point-free representation for probabilistic voxels and cumulative update of the planar uncertainty without caching original point clouds.
  2. On-demand voxel merging by taking advantage of the geometric features in the real world, accumulating voxels in a locality-sensitive hash and triggers merging lazily.

The paper is available on arxiv: C3P-VoxelMap: Compact, Cumulative and Coalescible Probabilistic Voxel Mapping

Dependency

ROS (tested on Noetic)

PCL (>= 1.8)

Eigen (>= 3.3.4)

livox_ros_driver, follow livox_ros_driver Installation.

Compilation

Clone the repository and compile it by catkin_make:

    mkdir -P ~/catkin_ws/src & cd ~/catkin_ws/src
    git clone https://github.com/deptrum/c3p-voxelmap.git
    cd ..
    catkin_make
    source devel/setup.bash

Running on Dataset

To run on dataset (KITTI dataset for example), firstly edit configuration file config/velodyne.yaml.

Besides general parameters such as point cloud topic name, there are some extra configutations concerning on-demand voxel merging. To enable voxel merging, set voxel_merging/enable_voxel_merging to true. The other parameters in voxel_merging can also be configured to adjust the effectiveness of on-demand voxel merging.

Optionally, set visualization/pub_merged_voxel to true to visualize voxel merging results. Merged voxel planes are shown with the same color in visualization.

After setting parameters, run the ROS package:

    cd ~/catkin_ws
    source devel/setup.bash
    roslaunch c3p_voxelmap mapping_velodyne.launch

In the meanwhile, play rosbag and the visualization results will be shown in RViz window.

Acknowledgments

Thanks for VoxelMap.