mobileroboticsskoltech / map-metrics Goto Github PK

Now, the most time consuming operation is iteration over points in point cloud, which could be parallelized.

Building Open3D takes eternity, there are definitely some packages which can be disabled

The reasons are well-described at https://py-pkgs.org/04-package-structure#the-source-layout

It will be useful for quick testing and performance measurments if library is able to run from command-line interface.

For example,
./map-metrics --pc="data/kitti_00" --tj="data/Tj_0" --metric="mme" [--"some common hyperparameters"]

It's build should be disabled by default

• Map Metrics version: 0.0.3
• Python version: >=3.6
• Operating System: MacOS

Description

Pip-package supports MacOS >=10.14 due to C++17 features.
We can downgrade to C++14, but a bit later :)

A \delta seems missing in Eq.6 of the paper. Have you tested on all the sequences and other dataset.
Recommend to ref LIBRE: The Multiple 3D LiDAR Dataset.
VLP64 may have a low precise for long distance measurement.

It takes an hour to build Open3D

Possible solutions:

• Add -j flag
• Specify Open3D build options
• Store Open3D files in Github Actions Cache

Configure CI to check whether C++ code is approved by cpplint.

• 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.