Currently integrated:
- Ubuntu 20.04 Focal Rosa
- Ros2 Foxy
- Autoware.Auto
- lgsvl_bridge
- lgsvl_msgs - the package delivering LGSVL message types for ROS
- package from this repo, which converts boundaries estimated by Autoware to the coordinates which can be properly rendered by LGSVL groundtruth viualizer.
- Running the node chain to estimate object boundaries with Autoware euclidian cluster implemenation
- Set up the following sensors in your vehicle
[
{
"type": "3D Ground Truth Visualizer",
"name": "3D Ground Truth Visualizer",
"params": {
"Topic": "/ar4development/lgsvl_detections"
},
"transform": {
"x": 0,
"y": 1.975314,
"z": -0.3679201,
"pitch": 0,
"yaw": 0,
"roll": 0
}
},
{
"type": "Lidar",
"name": "Lidar",
"params": {
"LaserCount": 32,
"MinDistance": 0.5,
"MaxDistance": 100,
"RotationFrequency": 10,
"FieldOfView": 41.33,
"CenterAngle": 10,
"Compensated": true,
"PointColor": "#ff000000",
"Topic": "/ar4development/points_raw",
"Frame": "velodyne",
"MeasurementsPerRotation": 360
},
"transform": {
"x": 0,
"y": 2.312,
"z": -0.3679201,
"pitch": 0,
"yaw": 0,
"roll": 0
}
},
{
"type": "GPS Odometry",
"name": "GPS Odometry",
"params": {
"Frequency": 12.5,
"Topic": "/ar4development/gps_odometry",
"Frame": "gps",
"IgnoreMapOrigin": true
},
"transform": {
"x": 0,
"y": 0,
"z": 0,
"pitch": 0,
"yaw": 0,
"roll": 0
}
}
]
- Clone this repo and build image from
Dockerfile
- Execute the image with port
9090
exposed to9090
- Run simulation using
BorregasAve
map and127.0.0.1:9090
as ROS connector - In simulator expan sensors panel and click "eye" icon against Ground Truth Visualizer sensor