ROS bridge for CARLA simulator

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.

Features

• [x] Cameras (depth, segmentation, rgb) support
• [x] Transform publications
• [x] Manual control using ackermann msg
• [x] Handle ROS dependencies
• [x] Marker/bounding box messages for cars/pedestrian
• [x] Lidar sensor support
• [x] Support CARLA synchronous mode
• [ ] Add traffic light support

Setup

Create a catkin workspace and install carla_ros_bridge package

#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

Start the ROS bridge

First run the simulator (see carla documentation: http://carla.readthedocs.io/en/latest/)

./CarlaUE4.sh -windowed -ResX=320 -ResY=240

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

Settings

You can setup the ros bridge configuration carla_ros_bridge/config/settings.yaml.

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.

Mode

Default Mode

In default mode (synchronous_mode: false) data is published:

• on every world.on_tick() callback
• on every sensor.listen() callback

Synchronous Mode

CAUTION: In synchronous mode, only the ros-bridge is allowed to tick. Other CARLA clients must passively wait.

In synchronous mode (synchronous_mode: true), the bridge waits for all sensor data that is expected within the current frame. This might slow down the overall simulation but ensures reproducible results.

Additionally you might set synchronous_mode_wait_for_vehicle_control_command to true to wait for a vehicle control command before executing the next tick.

Control Synchronous Mode

It is possible to control the simulation execution:

• Pause/Play
• Execute single step

The following topic allows to control the stepping.

A CARLA Control rqt plugin is available to publish to the topic.

Available ROS Topics

Ego Vehicle

Sensors

The ego vehicle sensors are provided via topics with prefix /carla/ego_vehicle/

Currently the following sensors are supported:

Camera

Lidar

GNSS

Collision Sensor

Lane Invasion Sensor

Object Sensor

Control

There are two modes to control the vehicle.

1. Normal Mode (reading commands from /carla/<ROLE NAME>/vehicle_control_cmd)
2. Manual Mode (reading commands from /carla/<ROLE NAME>/vehicle_control_cmd_manual)

This allows to manually override a Vehicle Control Commands published by a software stack. You can toggle between the two modes by publishing to /carla/<ROLE NAME>/vehicle_control_manual_override.

carla_manual_control makes use of this feature.

For testing purposes, 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_msgs/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_msgs/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

Additional way of controlling

CAUTION: This control method does not respect the vehicle constraints. It allows movements impossible in the real world, like flying or rotating.

You can also control the vehicle via publishing linear and angular velocity within a Twist datatype.

Currently this method applies the complete linear vector, but only the yaw from angular vector.

Carla Ackermann Control

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.

Other Topics

Object information of other actors

Status of CARLA

Walker

Other Vehicles

Debug Marker

It is possible to draw markers in CARLA.

Caution: Markers might affect the data published by sensors.

The following markers are supported in 'map'-frame:

• Arrow (specified by two points)
• Points
• Cube
• Line Strip

Carla Ego Vehicle

carla_ego_vehicle provides a generic way to spawn an ego vehicle and attach sensors to it. You can find further documentation here.

Carla Infrastructure Sensors

carla_infrastructure provides a generic way to spawn a set of infrastructure sensors defined in a config file. You can find further documentation here.

Waypoint calculation

To make use of the Carla waypoint calculation a ROS Node is available to get waypoints. You can find further documentation here.

Troubleshooting

ImportError: No module named carla

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.