Comments (2)
Hi bigbigpark,
This is the right place for these questions, thanks for your interest in the project !
So in the paper, we implemented the LoopClosure in pyLidar-SLAM.
Historically, pyLiDAR-SLAM was the main project where I could implement / benchmark SLAM algorithms,
We made a wrapper for CT-ICP in python and integrated it into pyLidar-SLAM.
Since then, (and really for time management of my PhD thesis), my focus has been on C++ code and ct_icp improvements.
So we are currently working on an implementation of the loop closure in C++ (with ROS support), as we found that it was more relevant in the short-term for most use-case of SLAM. It will probably appear in another gitlab project, but there will be pointers to it in this project. It should appear in the coming weeks (there is a working version which still needs some polishing).
In the mean time, you will find the LoopClosure implementation we used in our paper in pyLidarSLAM.
However our aim is (when I will have some time) to update the python wrapping to integrate ct-icp with pyLiDAR-SLAM, so we can use the neat parameter grid-search that comes with hydra.
So right now our SLAM (in this project) is really an odometry : ie correct locally, but no compensation for large trajectory errors.
Hope it answers your question,
Best Regards,
from ct_icp.
I totally understood what I didn't know. Thank you for your kind reply.
Thank you for sharing your wonderful project and giving good inspiration to many people.
Good luck.
from ct_icp.
Related Issues (20)
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from ct_icp.