Full-python LiDAR SLAM.
(if you find a C++ version of this repo, go to https://github.com/irapkaist/SC-LeGO-LOAM)
Thanks to the Scan Context, reverse loops can be successfully closed.
$ python3 main_icp_slam.py
The details of parameters are eaily found in the argparser in that .py file.
Those results are produced under the same parameter conditions:
Results (left to right):
Some of the results are good, and some of them are not enough. Those results are for the study to understand when is the algorithm works or not.
The Scan Context does not find loops well when there is a lane level change (i.e., KITTI 08, as below figures).
If the loop threshold is too low (0.07 in the below figure), no loops are detected and thus the odometry errors cannot be reduced.
If the loop threshold is high (0.20 in the below figure), false loops are detected and thus the graph optimization failed.
Giseop Kim ([email protected])
@JustWon - Supports Pangolin-based point cloud visualization along the SLAM poses. - Go to https://github.com/JustWon/PyICP-SLAM