A drawback of mom when dealing drafting walls in indoor envs.

[hahakid]

• 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.

[achains]

@hahakid We are sorry for the late response.
Thank you for your metric applicability research, you got an intriguing results.
We would love to continue the research and it would be great if you could provide the data you have used.
Data we need to start working on metrics:

• Point clouds
• Poses for those PCs

[hahakid]

@hahakid We are sorry for the late response. Thank you for your metric applicability research, you got an intriguing results. We would love to continue the research and it would be great if you could provide the data you have used. Data we need to start working on metrics:

• Point clouds
• Poses for those PCs

I am very sorry, I just left my job, so I did not restore the ros bag, but I uploaded the final map in pcd, and the trajectory coordinates in txt (quadruple notation), If you still needed it, please visite the google drive.
https://drive.google.com/file/d/1YUfgvniol6qtf1MdXgghxS4lQfws-KpY/view?usp=sharing

However, what I am trying to say is, maybe the MOM can be further improved based semantic information of the scene.