Velodyne VLP-16¶

Docker image version Docker image size

Simulation Setup¶

Add description in defined robot¶

Declared necessary argument and your own robot_gazebo.urdf.xacro

<xacro:arg name="gpu" default="false"/>
<xacro:arg name="organize_cloud" default="false"/>
<xacro:property name="gpu" value="$(arg gpu)" />
<xacro:property name="organize_cloud" value="$(arg organize_cloud)" />

Include the velodyne_description package

<xacro:include filename="$(find velodyne_description)/urdf/VLP16.urdf.xacro" />

Add LiDAR in the robot

<xacro:VLP-16 parent="base_footprint" name="velodyne" topic="/velodyne_points" organize_cloud="${organize_cloud}" hz="10" samples="440" gpu="${gpu}">
    <origin xyz="0 0 0.1" rpy="0 0 0" />
</xacro:VLP-16>

You could refer to more information from veloyne_simulator/velodyne_description/urdf/template.urdf.xacro

Launch LiDAR driver with simulated LiDAR¶

Launch example robot with LiDAR

ros2 launch velodyne_description example.launch.py

Launch the LiDAR data process without driver in another terminal

ros2 launch vlp_cartographer vlp_driver.launch.py is_sim:=True

Sample Robot¶

A given turtlebot waffle model with VLP-16 is provided in velodyne_simulator/velodyne_simulator/urdf/sample_robot.urdf.xacro

Launch the sample robot

ros2 launch velodyne_description example.launch.py robot:=1

LiDAR setup¶

Hardware Setup¶

Connect the LiDAR to power.
Connect the LiDAR to the computer or router using the provided ethernet cable.

Directly Using Computer¶

Connect the LiDAR to the computer using the ethernet cable.
Open the computer settings and navigate to Network > Wired.

Set the IPv4 configuration to 'manual' and configure the settings as shown in the image below:

Launch the Driver¶

Pipeline¶

Data process as following: raw data -> pointcloud -> laser scan -> slam method

Velodyne driver: velodyne_driver get the raw data from LiDAR.
Transform the raw data to pointcloud: velodyne_pointcloud
Transform the pointcloud to laser scan: velodyne_laserscan

Operating in a single launch file¶

ros2 launch vlp_cartographer vlp_driver.launch.py

By the above command, the driver, pointcloud and laserscan will be launched.

Published topics¶

Topic	Type	Description
`/velodyne_packets`	`velodyne_msgs/VelodyneScan`	raw data
`/velodyne_points`	`sensor_msgs/PointCloud2`	Point cloud message
`/scan`	`sensor_msgs/LaserScan`	laser scan message

Test with cartographer¶

In another terminal, launch the cartographer node:

ros2 launch vlp_cartographer cartographer_demo.launch.py

Bringup¶

Build the docker image and workspace
```
docker compose up --build
```

LiDAR driver

docker exec -it ros2-vlp-ws /home/ros2-essentials/vlp_ws/scripts/lidar-driver-bringup.sh

After launching the driver, launch the cartographer in another terminal

docker exec -it ros2-vlp-ws /home/ros2-essentials/vlp_ws/scripts/lidar-slam-bringup.sh