🥅 TraveSim

IEEE Very Small Size Soccer simulation project with ROS and Gazebo

Para a versão em PT-BR 🇧🇷 desse documento, veja aqui

📷 Screenshots
🎈 Intro
🌎 Worlds
📣 ROS topics
- ⬅ Input
  - Differential drive control (default)
  - Direct motor control
- ➡ Output
📏 Used models
- © Create your own model
🔧 Parameters
- 🚀 Roslaunch
📷 Virtual camera
📁 Folder structure
➕ Dependencies
- 🐍 Python virtual environment
🎨 Gazebo colors
📝 Contributing
✨ Contributors

📷 Screenshots

🎈 Intro

It is necessary to clone the project inside a catkin workspace. To create a workspace, refer to this link

To run the simulation with one controllable robot

roslaunch travesim simulation_robot.launch

To run the simulation with the entire team

roslaunch travesim simulation_team.launch

To run the simulation of a match

roslaunch travesim simulation_match.launch

🌎 Worlds

TraveSim can handle simulating games with 3 or 5 robots per team. The number of robots per team will be inferred from the chosen simulation world. The worlds currently supported are as follows:

vss_field.world - Base world for 3x3 matches
vss_field_camera.world - World for 3x3 matches with camera and spotlights
vss_field_5.world - Base world for 5x5 matches

So, for example, to run the simulation with a single team of 5 robots, run:

roslaunch travesim simulation_team.launch world_name:=vss_field_5.world

For more information about roslaunch parameters, see the 🚀 Roslaunch section.

📣 ROS topics

⬅ Input

The simulation can work using 2 input interfaces, differential drive control (default) or direct motor control. It is important to notice that is not possible to use both interfaces to control different robots at the same time.

Differential drive control (default)

By default, the simulation receives commands of type geometry_msgs/Twist, representing the desired velocity of the robot in two components: linear and angular.

# This expresses velocity in free space broken into its linear and angular parts.
Vector3  linear
Vector3  angular

The ROS topics follow the naming convention:

/yellow_team/robot_[0..2|0..4]/diff_drive_controller/cmd_vel
/blue_team/robot_[0..2|0..4]/diff_drive_controller/cmd_vel

The control of the robot is performed by the diff_driver_controller from the library ros_control. The controller represents the behavior of the embedded system of the robot and will send torque commands to the motors in order to follow the received set point.

The parameters of this controller are specified in the file ./config/motor_diff_drive.yml.

Direct motor control

The simulation also accepts control directly over angular velocity commands (in rad/s) for both robot's motors (through the interface velocity_controller from ros_control). This interface mimics a controller interface more coupled to the robots characteristics than differential drive control.

The commands are read from topics of type std_msgs/Float64, representing each motor's speed in rad/s

/yellow_team/robot_[0..2|0..4]/left_controller/command
/yellow_team/robot_[0..2|0..4]/right_controller/command
/blue_team/robot_[0..2|0..4]/left_controller/command
/blue_team/robot_[0..2|0..4]/right_controller/command

In order to enable this control interface, one should send the parameter twist_interface as false in roslaunch parameters

The parameters of this controller are specified in the file ./config/motor_direct_drive.yml.

➡ Output

By default, Gazebo publishes in the topic /gazebo/model_states of type gazebo_msgs/ModelStates, with an array of informations about each model in the simulation.

# broadcast all model states in world frame
string[] name                 # model names
geometry_msgs/Pose[] pose     # desired pose in world frame
geometry_msgs/Twist[] twist   # desired twist in world frame

For convenience, this package have a script (vision_proxy.py) that subscribes this topic and republishes the information at different topics of type gazebo_msgs/ModelState for each entity (3 yellow team robots, 3 blue team robots and 1 ball, 7 in total).

# Set Gazebo Model pose and twist
string model_name           # model to set state (pose and twist)
geometry_msgs/Pose pose     # desired pose in reference frame
geometry_msgs/Twist twist   # desired twist in reference frame
string reference_frame      # set pose/twist relative to the frame of this entity (Body/Model)
                            # leave empty or "world" or "map" defaults to world-frame

The republished topics are

/vision/yellow_team/robot_[0..2|0..4] - Yellow team robots's topics
/vision/blue_team/robot_[0..2|0..4] - Blue team robots's topics
/vision/ball - Ball's topic

All units are SI, distances are measured in meters, angles in radians, linear velocity in m/s and angular velocity in rad/s.

📏 Used models

The simulation is build upon a generic vss robot (more details here), inspired by VSS SDK model.

As support, models were created for the VSS field and ball, both build from Robocore's rules for IEEE VSS.

© Create your own model

To create a model for your project, refer to:

Phobos - Generate urdf files from Blender
SW2URDF - Generate urdf files from SolidWorks
fusion2urdf - Generate urdf files from Fusion 360
ROS wiki - How build a urdf model from scratch

To use your custom model, change the value of the model parameter when launching the simulation.

🔧 Parameters

🚀 Roslaunch

world_name - Name of world file inside ./worlds folder, default "vss_field.world"
model - Path of simulated robot model, default "./urdf/vss_robot.xacro"
controller_config_file - Path of simulated robot controllers config file, default "./config/motor_diff_drive.yml" if twist_interface is true, "./config/motor_direct_drive.yml" otherwise
ros_control_config_file - Path of gazebo_ros_control config file, default "./config/ros_control_config.yml"
debug - Enable debug messages in terminal, default "false"
gui - Enable Gazebo's GUI window, default "true"
paused - Init simulation paused, default "true"
use_sim_time - Use simulated time as reference in messages, default "true"
recording - Enable Gazebo's state log, default "false"
keyboard - Enable joystick/keyboard control node, default "false"
twist_interface - Enable geometry_msgs/Twist interface if true, 2 std_msgs/Float64 control interface otherwise. Default "true". See the docs for more info.

To pass a parameter to the simulation, just write the parameter name and its new value with :=

For example, to change the parameter keyboard to true:

roslaunch travesim simulation_team.launch keyboard:=true

📷 Virtual camera

The simulation has a virtual camera that record images from the top of the field, in the same way as a real VSS match. To enable it, one should use the world file vss_field_camera.world

roslaunch travesim simulation_team.launch world_name:=vss_field_camera.world

The images are published in the topic /camera/image_raw

It is possible to watch the footage with the package image_view

rosrun image_view image_view image:=/camera/image_raw

📁 Folder structure

bagfiles/ - Folder to store recorded bagfiles
docs/ - Documentation files
launch/ - Roslaunch files written in ROS XML syntax
meshes/ - .stl files for vss_generic_robot, created with SolidWorks SW2URDF extension
models/ - Custom Gazebo models used inside the simulation, as the field and the VSS ball
scripts/ - Python scripts used in the project
- keyboard_node.py - Pygame script to capture keyboard or joystick input to control the simulation
- vision_proxy.py - Script to split gazebo_msgs/ModelStates array in several gazebo_msgs/ModelState topics
urdf/ - Robot description files in .urdf and .xacro format. The .urdf files were generated with SolidWorks SW2URDF extension
worlds/ - World files in SDL format

➕ Dependencies

The simulation is develop for ROS and Gazebo, it is recommend to install both with:

sudo apt install ros-noetic-desktop-full

The project depends on the package velocity_controllers and effort_controllers in the library ros_controllers and the python library pygame. It is possible to install both with apt-get

sudo apt install ros-noetic-velocity-controllers ros-noetic-effort-controllers python3-pygame

Or using rosdep

rosdep install travesim

🐍 Python virtual environment

One may want to run the project inside a python virtualenv, after all this is a good practice in the python development book

You can create a python environment with the command

python3 -m venv venv

Then you should run source in the virtual environment

source ./venv/bin/activate

To install the dependencies, run the command

pip install -r requirements.txt

Some external libraries may be missing to build pygame package. You can install then with

sudo apt-get install
  subversion \
  ffmpeg \
  libsdl1.2-dev \
  libsdl-image1.2-dev \
  libsdl-mixer1.2-dev \
  libsdl-ttf2.0-dev \
  libavcodec-dev \
  libavformat-dev \
  libportmidi-dev \
  libsmpeg-dev \
  libswscale-dev \

🎨 Gazebo colors

For a list of default available color in Gazebo, refer to the config file in the oficial repo. We have also 2 OGRE scripts team blue and team yellow for custom colors definition (Gazebo ref and OGRE ref)

📝 Contributing

Any help in the development of robotics is welcome, we encourage you to contribute to the project! To learn how, see the contribution guidelines here.

✨ Contributors

Thanks goes to these wonderful people (emoji key):

_{Felipe Gomes de Melo} 📖 👀 💻 🌍	_{Lucas Haug} 👀 💻 🌍 📖	_tocoquinho 🤔 📖	_{Bernardo Coutinho} 👀 💻 📖	_{Lucas Schneider} 👀 💻 🌍 📖	_{Júlia Mello} 🎨 🔣	_{ThallesCarneiro} 🎨 🔣
_{TetsuoTakahashi} 🤔	_{Gabriel Cosme Barbosa} 👀	_RicardoHonda 👀	_{leticiakimoto} 👀