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<h1>MapClosures</h1>
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<a href="https://github.com/PRBonn/MapClosures/blob/main/README.md#Install">Install</a>
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<a href=https://www.ipb.uni-bonn.de/pdfs/gupta2024icra.pdf>ICRA24 Paper</a>
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<a href=https://github.com/PRBonn/MapClosures/issues>Contact Us</a>
Effectively Detecting Loop Closures using Point Cloud Density Maps.
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.
target_link_libraries(my_target PUBLIC map_closures)
#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
Providing the -v flag will initialize the visualizer:
map_closure_pipeline -v
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
$ claude mcp add MapClosures \
-- python -m otcore.mcp_server <graph>