Create map for autoware

[shmpwk]

Hi, we want map for autoware planning simulation.
There is a prepared map in the tutorial, which contains pcd and osm.

We know osm is a Lanelet2 Format and it is made from Vector Map Builder
We would appreciate it if you could teach us how to get pcd with or without your tools.

Environment: Ubuntu20.04, ROS2 galactic

[angry-crab]

Any open source slam algorithm would be able to give a pcd map if a rosbag or other format of sensor data are provided. Some choices are listed below.

HDL
LIO-SAM

[shmpwk]

Thank you for your information!
We also consider to use interactive slam, which includes HDL,
However interactive slam supports neither ROS2 nor ROS1 noetic, and only supports melodic or its less version.
So we decide to use LIO-SAM which supports ROS2.

[shmpwk]

As @emi0116 says, LIO-SAM is a little complicated.
It is better for us to use the easiest slam this time.
So finally, we use lidarslam_ros2.

[emi0116]

Hello.
You have an interesting discussion.
The feature-based slams proposed by loam (lego-loam, lio-sam, etc.) are very fast and good for real-time mapping, but I would not recommend using them for map matching because the maps are very blurry.
If you can use ROS1, I suggest you use hdl_graph_slam or interactive_slam.
For ROS2, I have used lidarslam_ros2(https://github.com/rsasaki0109/lidarslam_ros2), which is also good
(There was talk that it would also be used in navigation2, but it appears that work has now stopped.
ros-navigation/navigation2#1757
)

[shmpwk]

Thanks for the extremely useful information!
We use ROS2 and prefer accuracy to speed and real-time performance since we are working on a prototype project.
So lidarslam_ros2 seems nice for us except stopping their work.

[emi0116]

My comment was confusing.
It appears that the development of lidarslam_ros2 is continuing, just that the move to make it the standard SLAM for ROS2 has stopped. (At least the maintainer seems to be actively commenting on issues.)

[shmpwk]

We finished making map by only using lidar. Thank you!