This ROS package aims at providing a simple ROS bridge for CARLA simulator.
Important Note: This documentation is for CARLA versions newer than 0.9.4.
- Cameras (depth, segmentation, rgb) support
- Transform publications
- Manual control using ackermann msg
- Handle ROS dependencies
- Marker/bounding box messages for cars/pedestrian
- Lidar sensor support
- Rosbag in the bridge (in order to avoid rosbag record -a small time errors)
- Add traffic light support
#setup folder structure
mkdir -p ~/carla-ros-bridge/catkin_ws/src
cd ~/carla-ros-bridge
git clone https://github.com/carla-simulator/ros-bridge.git
cd catkin_ws/src
ln -s ../../ros-bridge
source /opt/ros/kinetic/setup.bash
cd ..
#install required ros-dependencies
rosdep update
rosdep install --from-paths src --ignore-src -r
#build
catkin_make
For more information about configuring a ROS environment see http://wiki.ros.org/ROS/Tutorials/InstallingandConfiguringROSEnvironment
First run the simulator (see carla documentation: http://carla.readthedocs.io/en/latest/)
./CarlaUE4.sh -windowed -ResX=320 -ResY=240 -benchmark -fps=10
Wait for the message:
Waiting for the client to connect...
Then start the ros bridge (choose one option):
export PYTHONPATH=$PYTHONPATH:<path/to/carla/>/PythonAPI/<your_egg_file>
source ~/carla-ros-bridge/catkin_ws/devel/setup.bash
# Option 1: start the ros bridge
roslaunch carla_ros_bridge carla_ros_bridge.launch
# Option 2: start the ros bridge together with RVIZ
roslaunch carla_ros_bridge carla_ros_bridge_with_rviz.launch
# Option 3: start the ros bridge together with an example ego vehicle
roslaunch carla_ros_bridge carla_ros_bridge_with_example_ego_vehicle.launch
You can setup the ros bridge configuration carla_ros_bridge/config/settings.yaml.
As we have not spawned any vehicle and have not added any sensors in our carla world there would not be any stream of data yet.
You can make use of the CARLA Python API script manual_control.py.
cd <path/to/carla/>
python manual_control.py --rolename=ego_vehicle
This spawns a carla client with role_name='ego_vehicle'.
If the rolename is within the list specified by ROS parameter /carla/ego_vehicle/rolename, the client is interpreted as an controllable ego vehicle and all relevant ROS topics are created.
To simulate traffic, you can spawn automatically moving vehicles by using spawn_npc.py from CARLA Python API.
| Topic | Type |
|---|---|
/carla/<ROLE NAME>/odometry |
nav_msgs.Odometry |
The ego vehicle sensors are provided via topics with prefix /carla/ego_vehicle/<sensor_topic>
Currently the following sensors are supported:
| Topic | Type |
|---|---|
/carla/<ROLE NAME>/camera/rgb/<SENSOR ROLE NAME>/image_color |
sensor_msgs.Image |
/carla/<ROLE NAME>/camera/rgb/<SENSOR ROLE NAME>/camera_info |
sensor_msgs.CameraInfo |
| Topic | Type |
|---|---|
/carla/<ROLE NAME>/lidar/<SENSOR ROLE NAME>/point_cloud |
sensor_msgs.PointCloud2 |
| Topic | Type |
|---|---|
/carla/<ROLE NAME>/gnss/front/gnss |
sensor_msgs.NavSatFix |
| Topic | Type |
|---|---|
/carla/<ROLE NAME>/collision |
carla_msgs.CarlaCollisionEvent |
| Topic | Type |
|---|---|
/carla/<ROLE NAME>/lane_invasion |
carla_msgs.CarlaLaneInvasionEvent |
| Topic | Type |
|---|---|
/carla/<ROLE NAME>/vehicle_control_cmd (subscriber) |
carla_msgs.CarlaEgoVehicleControl |
/carla/<ROLE NAME>/vehicle_status |
carla_msgs.CarlaEgoVehicleStatus |
/carla/<ROLE NAME>/vehicle_info |
carla_msgs.CarlaEgoVehicleInfo |
You can stear the ego vehicle from the commandline by publishing to the topic /carla/<ROLE NAME>/vehicle_control_cmd.
Examples for a ego vehicle with role_name 'ego_vehicle':
Max forward throttle:
rostopic pub /carla/ego_vehicle/vehicle_control_cmd carla_ros_bridge/CarlaEgoVehicleControl "{throttle: 1.0, steer: 0.0}" -r 10
Max forward throttle with max steering to the right:
rostopic pub /carla/ego_vehicle/vehicle_control_cmd carla_ros_bridge/CarlaEgoVehicleControl "{throttle: 1.0, steer: 1.0}" -r 10
The current status of the vehicle can be received via topic /carla/<ROLE NAME>/vehicle_status.
Static information about the vehicle can be received via /carla/<ROLE NAME>/vehicle_info
In certain cases, the Carla Control Command is not ideal to connect to an AD stack.
Therefore a ROS-based node carla_ackermann_control is provided which reads AckermannDrive messages.
You can find further documentation here.
| Topic | Type |
|---|---|
/carla/objects |
derived_object_msgs.ObjectArray |
Object information of all vehicles, except the ego-vehicle(s) is published.
| Topic | Type |
|---|---|
/carla/map |
std_msgs.String |
The OPEN Drive map description is published.
carla_ego_vehicle provides a generic way to spawn an ego vehicle and attach sensors to it. You can find further documentation here.
To make use of the Carla waypoint calculation a ROS Node is available to get waypoints. You can find further documentation here.
The carla_ros_bridge could also be used to record all published topics into a rosbag:
roslaunch carla_ros_bridge client_with_rviz.launch rosbag_fname:=/tmp/save_session.bag
This command will create a rosbag /tmp/save_session.bag
You can of course also use rosbag record to do the same, but using the ros_bridge to do the recording you have the guarentee that all the message are saved without small desynchronization that could occurs when using rosbag record in an other process.
You're missing Carla Python. Please execute:
export PYTHONPATH=$PYTHONPATH:<path/to/carla/>/PythonAPI/<your_egg_file>
Please note that you have to put in the complete path to the egg-file including the egg-file itself. Please use the one, that is supported by your Python version. Depending on the type of CARLA (pre-build, or build from source), the egg files are typically located either directly in the PythonAPI folder or in PythonAPI/dist.
Check the installation is successfull by trying to import carla from python:
python -c 'import carla;print("Success")'
You should see the Success message without any errors.
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