The document provides an introduction to using the Gazebo simulator for robotcar simulation in ROS, including building a basic simulation environment, defining a robot model, and adding wheels and Ackermann steering; it also discusses potential next steps like simulating sensors and developing a steering algorithm.

1. First steps
with Gazebo simulation
for Robocar
Sergey Matyunin
August 2020

2. Plan
● Motivation
● Intro to ROS
● Building a simulation for roborace in Gazebo
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3. Motivation
● Preparing for robocar competition 2019
○ Meetup
○ First steps with robotics
○ Low-cost self driving car
● Donkeycar software
○ https://www.donkeycar.com/
○ Easy to start with
○ Active community
○ Specialized software stack
● Robot Operating System (ROS)
○ flexible framework for writing robot software.
○ It is a collection of tools, libraries, and conventions
○ https://www.ros.org/about-ros/
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https://www.donkeycar.com/

4. ROS: Overview
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5. How does ROS look like?
● Set up environment
● Write code with ROS libraries in C++ or
python
○ Use built-in modules as building blocks
○ Define message types
○ Write configs
● Launch
● Use visualization and debug tools
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…
…

6. Projects with ROS
● Robocar
○ github V1 - race 2019, wiki
○ github V2 (ongoing)
● Project Omicron
○ target: https://www.robocup.org/
○ blog https://project-omicron.github.io/
○ code https://github.com/project-omicron/
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7. Porting Donkeycar to ROS
● Inspiration
○ Donkeycar
○ Project Omicron
○ ….
● Hardware was customized a bit
● ROS for Raspberry Pi
○ Installing ROS Kinetic on the Raspberry Pi
○ ROS melodic on Raspberry Pi 3 B+
● Robocar on github
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8. Why simulation
● I had two projects ongoing, when Corona happened
● How to develop if you don’t have hardware at hand?
● Donkeycar simulator
○ https://github.com/tawnkramer/sdsandbox
○ Learning to Drive Smoothly in Minutes
● Gazebo simulator
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9. What is Gazebo
● Gazebo is an open-source 3D robotics simulator.
○ Physics engine
○ 3D rendering
○ Sensor simulation
○ Integration with ROS
● Let’s launch some simulation (video)
○ $ sudo apt-get install ros-<distro>-husky-simulator
○ $ source /opt/ros/melodic/setup.bash
○ $ export HUSKY_GAZEBO_DESCRIPTION=$(rospack find husky_gazebo)/urdf/description.gazebo.xacro
○ $ roslaunch husky_gazebo husky_playpen.launch kinect_enabled:=true
○ In another terminal to check that the sensors work
# activate ROS
$ rqt_image_view
○ In another terminal to control
# activate ROS
rosrun teleop_twist_keyboard teleop_twist_keyboard.py
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10. Another example
● Project Omicron https://github.com/project-omicron/gazebo_simulation
○ Check out the README, install the dependencies.
○
○ Controlling
cd ~/catkin_ws/ && source devel/setup.bash
rosrun teleop_twist_keyboard teleop_twist_keyboard.py
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11. Another example
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12. Resources for learning
● Tutorials
○ http://wiki.ros.org/urdf_tutorial
○ http://gazebosim.org/tutorials
● Learning by copying
○ turtlebot3 https://emanual.robotis.com/docs/en/platform/turtlebot3/simulation/
○ husky http://wiki.ros.org/husky_gazebo/Tutorials/Simulating%20Husky
○ husky + slam https://github.com/incebellipipo/carto_demo
● More advanced examples
○ https://github.com/AutoRally/autorally
○ https://mushr.io/tutorials/intro-to-ros/
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13. Simulation for robocar race
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14. Simulation for robocar race
├──
├──
│ └──
├──
└──
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15. changing package.xml
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16. launch file
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17. launch file - results
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18. Defining the (empty) world
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19. Defining the (empty) world
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20. Defining a robot
To define a robot we have to describe all the parts (aka links) and connections
between them (aka joints).
Ros and Gazebo take care of
● geometrical transformations (tf module),
● physics simulation and rendering.
http://wiki.ros.org/navigation/Tutorials/RobotSetup/TF 20

21. Defining a robot - URDF/XACRO (not working)
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22. Defining a model - XACRO for Gazebo
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23. Defining a model - Updating launch file
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24. Defining a model - Results
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25. Defining a model - Results
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26. Let’s add some wheels - XACRO update
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27. Let’s add some wheels - launch.xml
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28. Let’s add some wheels - controller
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29. Launching
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30. A realistic car with Ackermann steering
https://en.wikipedia.org/wiki/Ackermann_steering_geometry
https://github.com/trainman419/ackermann_vehicle-1, blog post
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31. A realistic car with Ackermann steering
Changes in launch file:
<node name="controller_spawner" pkg="controller_manager" type="spawner"
args="$(arg joint_params)" output="screen"/>
<!-- Control the steering, axle, and shock absorber joints. -->
<node name="ackermann_controller" pkg="robocar_simulation"
type="ackermann_controller.py"
output="screen">
<param name="cmd_timeout" value="$(arg cmd_timeout)"/>
<rosparam file="$(find robocar_simulation)/config/em_3905_ackermann_ctrlr_params.yaml"
command="load"/>
</node>
<!-- required to get geometrical transformations from ackermann_controller -->
<node name="vehicle_state_publisher" pkg="robot_state_publisher" type="robot_state_publisher">
<param name="publish_frequency" value="30.0"/>
</node>
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32. A realistic car with Ackermann steering
Publishing ackermann_msgs:
roslaunch robocar_simulation robocar_sim.launch model:=$(rospack find
robocar_ackermann_description)/urdf/car.xacro joint_params:=$(rospack find
robocar_simulation)/config/em_3905_joint_ctrlr_params.yaml
Results:
https://www.youtube.com/watch?v=oXl0L4rbr3o
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33. Defining the track
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https://github.com/project-omicron/gazebo_simulation

34. Defining the track
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35. Defining the track
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└──
├──
│ ├──
│ │ ├──
│ │ └──
│ └──
│ ├──
│ ├──
│ └──
├──
├──
├──
├──
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└──

36. Defining the track (model.sdf)
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37. Defining the track (3d model and materials)
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38. Results
https://youtu.be/vllWGL7J_i8
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39. What is missing?
● Simulating sensors
○ Raspberry pi camera
https://github.com/UbiquityRobotics/raspic
am_node.git
○ Realsense camera
https://github.com/SyrianSpock/realsense_
gazebo_plugin.git
○ Lidar
http://gazebosim.org/tutorials?tut=add_las
er#AddingaLaser
○ IMU
http://wiki.ros.org/hector_gazebo_plugins
○ Some usage examples:
https://github.com/project-omicron/gazebo
_simulation
● Algorithm of the robot steering
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40. Possible future topics
● More about ROS
● ROS on Arduino
● Simultaneous localization and mapping (SLAM)
○ Basics
○ SLAM in ROS
● Sensors simulation for Gazebo
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41. Join us!
Autonomous Mobility Slack channel
https://join.slack.com/t/autonom-mobility/shared
_invite/zt-2srteszk-KUI6yVDE33PXo9xE_f1JXw
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Advanced Computer Vision Study Group
https://www.meetup.com/advanced-computer-vision/
https://advancedcomputervision.github.io/
Scope: reading and discussing state of the art papers
First topic: Unsupervised depth estimation
Paper: 3D Packing for Self-Supervised Monocular Depth
Estimation, by Vitor Guizilini et al, 2020