3. Problem domain: Traffic network of Dubins cars

Often referred to as “the second domain,” the basic setting is navigation in a small network of roads with vehicles that follow unicycle-like dynamics. Every road network is a 4-connected grid, subject to a rigid-body transformation: as such, the segments may not be axis-aligned.

3.1. Preparations

While below we include pointers to the main websites for dependencies, many are available via packages for your OS and may already be installed, especially if you have ROS on Ubuntu 14.04. Supported platforms are described in the Introduction.

3.1.1. Basic

There are two major variants of this benchmark: one based in simulation and another on a physical testbed. We begin with preparations appropriate for both.

On Ubuntu, Eigen can be obtained by installing the “libeigen3-dev” deb package (https://packages.debian.org/jessie/libeigen3-dev).

Several ROS packages for the Kobuki by Yujin Robot are required.

Install fmrb from your copy of the repository, e.g.,

cd tools/fmrb-pkg
pip install -e .

or get it from PyPI,

pip install fmrb

3.1.2. Dependencies of the simulation variant

3.1.3. Dependencies of the physical variant


3.1.4. Supplementary prerequisites

As for the Problem domain: Scaling chains of integrators, there is code that is relevant but not required for this benchmark.

Teleoperation of the vehicle to be controlled can be achieved using kobuki_keyop ROS package. An example demonstrating a configuration known to work in the simulation variant:

roslaunch dubins_traffic_utils teleop.launch

3.2. Tutorials

In the below code, $FMRBENCHMARK is the absolute path to a copy of the fmrbenchmark repository on your machine.

3.2.1. Demonstrations of components

To build the “standalone” (i.e., independent of ROS) examples demonstrating various parts of this benchmark, go to the dubins_traffic_utils directory ($FMRBENCHMARK/domains/dubins_traffic/dubins_traffic_utils) and then follow the usual CMake build instructions. On Unix without an IDE, usually these are

mkdir build
cd build
cmake ..

One of the resulting programs is genproblem, the source of which is $FMRBENCHMARK/domains/dubins_traffic/dubins_traffic_utils/examples/standalone/genproblem.cpp. The output is a problem instance in JSON. To visualize it, try

dubins_traffic_utils/build/genproblem dubins_traffic_utils/examples/trialsconf/mc-small-4grid-agents2.json | analysis/plotp.py -

from the directory $FMRBENCHMARK/domains/.

3.2.2. Launching a problem instance of the simulation variant

Create a catkin workspace.

mkdir -p dubsim_workspace/src
cd dubsim_workspace/src

Create symbolic links to the ROS packages in the fmrbenchmark repository required for this example.

ln -s $FMRBENCHMARK/domains/integrator_chains/integrator_chains_msgs
ln -s $FMRBENCHMARK/domains/dubins_traffic/dubins_traffic_msgs
ln -s $FMRBENCHMARK/domains/dubins_traffic/dubins_traffic_utils
ln -s $FMRBENCHMARK/domains/dubins_traffic/dub_sim
ln -s $FMRBENCHMARK/domains/dubins_traffic/e-agents/wander
ln -s $FMRBENCHMARK/examples/dubins_traffic_examples

Build and install it within the catkin workspace.

cd ..
catkin_make install

Because the installation is local to the catkin workspace, before beginning and whenever a new shell session is created, you must first

source install/setup.zsh

where the source command assumes that you are using the Z shell; try setup.bash if you use Bash.

Finally, launch a small 4-grid road network with two adversarially controlled vehicles, also known as e-agents (where ``e’’ abbreviates ``environment’‘).

python $FMRBENCHMARK/domains/dubins_traffic/trial-runner.py -f mydata.json $(rospack find dubins_traffic_utils)/examples/trialsconf/mc-small-4grid-agents2.json

This will cause trial data to be saved to the file mydata.json in the local directory from where the above command is executed.

The Gazebo server is launched without a GUI frontend, which is also known as running headless. A local viewer can be launched using


The vehicle to be controlled has the ROS namespace /ego. The e-agents have namespaces defined in the trials configuration file. In the example mc-small-4grid-agents2.json used in this tutorial, these are /agent0 and /agent1.

In a separate terminal, run your controller. For example, assuming your controller is contained in the package your_controller with launch file foo.launch, in a separate terminal, run

roslaunch your_controller foo.launch

You can run an example controller using:

roslaunch dubins_traffic_examples simple.launch

This is a simple controller that sets the ego vehicle’s forward and angular velocity based on the next goal to be visited, and cycles through goals in this manner.

Support code for working with road network descriptions is available in roadnet.hpp and dubins_traffic.py.

For example, try

analysis/plotp.py dubins_traffic_utils/examples/data/square.json

from the directory $FMRBENCHMARK/domains/dubins_traffic/.