A drawback of mom when dealing drafting walls in indoor envs. #19
Description
- Map Metrics 0.0.1:
- Python version 3.8:
- Operating System win10:
Description
It tired the metirc on a small scale data, likely a room with differential chassis and a RS-16.
When the point cloud map consists of multiple wall (actually one) caused by drifting, the mom metric may have a smaller value than a normal map.
I think it is caused by the orthogonal walls (both the real one and drifted one) and floor.
Specifically, Fig.1 is generated by LOAM (without drift), and Fig. 2 is gererated by Lio-sam (with draft).
I also considered to downsample the two maps into the same scale with voxel downsampling. The results are listed below.
I think this kind of problem is very familiar for indoor, I have seen many drafting wall during daily usage of lidar based slam, without semantic labels, it is very hard for distinguishing them automatically.
What I Did
I will try the 0.0.2 version later.
Paste the command(s) you ran and the output.
If there was a crash, please include the traceback here.