• Install • ICRA24 Paper • Contact Us
Effectively Detecting Loop Closures using Point Cloud Density Maps.
- Include the following snippet in your project's
CMakeLists.txt
:
set(USE_SYSTEM_EIGEN3 ON CACHE BOOL "use system eigen3")
set(USE_SYSTEM_OPENCV ON CACHE BOOL "use system opencv")
include(FetchContent)
FetchContent_Declare(
map_closures
GIT_REPOSITORY https://github.com/PRBonn/MapClosures.git
GIT_TAG main
SOURCE_SUBDIR cpp
)
FetchContent_MakeAvailable(map_closures)
You can trigger the automatic installation of the dependencies by playing around with the options in the first three lines of the snippet.
- Link MapClosures against your library or executable:
target_link_libraries(my_target PUBLIC map_closures)
- The following include directive in your source code file will provide access to the core API of MapClosures:
#include <map_closures/MapClosures.hpp>
pip install map-closures
The following command will provide details about how to use our pipeline:
map_closure_pipeline --help
map_closure_pipeline --help
If you use this library for any academic work, please cite our original paper.
@inproceedings{gupta2024icra,
author = {S. Gupta and T. Guadagnino and B. Mersch and I. Vizzo and C. Stachniss},
title = {{Effectively Detecting Loop Closures using Point Cloud Density Maps}},
booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
year = {2024},
codeurl = {https://github.com/PRBonn/MapClosures},
}
As we decided to continue the development of MapClosures beyond the scope of the ICRA paper, we created a git tag
so that researchers can consistently reproduce the results of the publication. To checkout at this tag, you can run the following:
git checkout ICRA2024
Our development aims to push the performances of MapClosures above the original results of the paper.
This repository is heavily inspired by, and also depends on KISS-ICP