- Load a lidar point cloud datum from KITTI dataset
- Perform octree-based nearest neighbor search
- Make voxel map based on Octomap library
- Fast voxel mapping using Bonxai library, and visualize the map
Requirement: PCL, Octomap
mkdir build && cd build
cmake ..
make -j
./octree
./octomap_kitti
Requires base build
docker build . -t slam:4_9
docker run -it --env DISPLAY=$DISPLAY -v `pwd`/results:/fastcampus_slam_codes/4_9/results -v /tmp/.X11-unix/:/tmp/.X11-unix:ro slam:4_9
# Inside docker container
cd fastcampus_slam_codes/4_9
./build/octree
./build/octomap_kitti
Fast voxel mapping using Bonxai library
docker build . -f Dockerfile_bonxai -t slam:4_9_bonxai
docker run -it --env DISPLAY=$DISPLAY -v /kitti:/data -v /tmp/.X11-unix/:/tmp/.X11-unix:ro slam:4_9_bonxai
# Inside container
cd Bonxai/build/bonxai_map/benchmark
./benchmark_kitti --clouds /data/sequences/00/velodyne/ --calib /data/sequences/00/calib.txt --poses /data/poses/00.txt
exit
# Outside container
docker cp <container_id>:/Bonxai/build/bonxai_map/benchmark/bonxai_result.pcd ./results/bonxai_result.pcd
# Visualization
pip3 install open3d numpy
python3 pcd_viewer.py ./results/bonxai_result.pcd