Robot simulation is an essential tool in every roboticist's toolbox. A well-designed simulator makes it possible to rapidly test algorithms, design robots, perform regression testing, and train AI system using realistic scenarios. Gazebo offers the ability to accurately and efficiently simulate populations of robots in complex indoor and outdoor environments. At your fingertips is a robust physics engine, high-quality graphics, and convenient programmatic and graphical interfaces. Best of all, Gazebo is free with a vibrant community.
Autonomous vehicles, and the hardware and software required to operate these vehicles, are a hot topic of conversation. At Open Robotics, we thought it would be a great time to showcase Gazebo in the autonomous vehicle domain.
We built a fictitious world consisting of a handcrafted (via GIMP) terrain, and numerous freely available models on the Gazebo Model Database. Our vehicle of choice is a Prius Hybrid, the model of which consists of a power-train and full kinematic and dynamic simulation. Human models were also placed in the world to act as pedestrians.
You can find the source code for the city environment at https://bitbucket.org/osrf/citysim. This repository contains the world description, and a few plugins for traffic light control and visual effects.
The citysim code is a work in progress. It will be ready for public consumption when Gazebo 9 is released in January 2018.
While most of the capabilities required to run this demonstration exist in Gazebo8, we did leverage a few new capabilities, such as a joystick interface, that will appear in Gazebo9. Therefore, the citysim branch of Gazebo is also required.
Gazebo has many other tools and features to support autonomous vehicle testing and development. One such tool is real-time plotting of simulation data, as demonstrated in the following video.
Have fun simulating your world!
Utilizing OGRE, Gazebo provides realistic rendering of environments including high-quality lighting, shadows, and textures.
Generate sensor data, optionally with noise, from laser range finders, 2D/3D cameras, Kinect style sensors, contact sensors, force-torque, and more.
Develop custom plugins for robot, sensor, and environmental control. Plugins provide direct access to Gazebo's API.
Many robots are provided including PR2, Pioneer2 DX, iRobot Create, and TurtleBot. Or build your own using SDF.
Run simulation on remote servers, and interface to Gazebo through socket-based message passing using Google Protobufs.
Extensive command line tools facilitate simulation introspection and control.
A simple set of steps to get Gazebo up and running rapidly.
Description of Gazebo's hotkeys and mouse interactions.
The best way to start using Gazebo is to run through the tutorials. These tutorials cover both basic and simple concepts through a series of exercises.
If you can't find what you are looking for, try our askbot help forum located at answers.gazebosim.org.
Want to exchange ideas with the rest of the community? Come to community.gazebosim.org.
A high-level description of Gazebo and its various components.
Doxygen generated documentation for the Gazebo libraries.
A complete list of all the protobuf messages used by Gazebo
SDFormat is an XML file format that defines environments and models. This specification defines all the XML elements for describing world and models.
Gazebo will release a new major version once a year on the last week of January. Even numbered releases will have a life-span of two years, and odd five years.
The following roadmap is a best guess at the available features for each version. At the time of release more or fewer features may be available.
Refer documentation in downstream applications, such as ROS, for version compatiblilty.
A tick-tock release cycle allows easy migration to new software versions. Obsolete Gazebo code is marked as deprecated for one major release. Deprecated code produces compile-time warnings. These warning serve as notification to users that their code should be upgraded. The next major release will remove the deprecated code.
Example where function foo is deprecated and replaced by function bar:
|Gazebo v1.0||Gazebo v2.0||Gazebo v3.0|
|Lines of code||186k||197k||214k||217k||231k||266k||298k|
|Lines of comments||57k||63k||68k||69k||75k||89k||99k|
|Test function coverage||45.7%||47.1%||41.3%||40.6%||48.7%||47.9%||52.9%|
|Test branch coverage||32.2%||35.5%||29.2%||27.6%||38.0%||39.1%||44.5%|
Gazebo supports the ODE, Bullet, Simbody and DART physics engines. By default Gazebo is compiled with support for ODE. In order to use the other engines, first make sure they are installed and then compile Gazebo from source.
|Physics Engine||Gazebo Version||Availability||Notes|
|ODE||1.9+||Binary,Source||Default engine. Gazebo maintains a fork of ODE which has diverged from the upstream package.|
|Bullet||3.0+||Source||Gazebo requires libbullet2.82, available in the OSRF repository and to be included in Ubuntu Utopic.|
|Simbody||3.0+||Source||Simbody packages are hosted in the OSRF repository. Expected to appear in Ubuntu Utopic official repositories.|
|DART||3.0+||Source||DART packages are hosted in dartsim PPA. DART is in the process of moving toward inclusion in Ubuntu.|
We are developing a physics plugin framework to resolve dependency issues. Each physics engine will interface to Gazebo through a plugin, avoiding the need to compile Gazebo with support for each engine.
Gazebo development began in the fall of 2002 at the University of Southern California. The original creators were Dr. Andrew Howard and his student Nate Koenig. The concept of a high-fidelity simulator stemmed from the need to simulate robots in outdoor environments under various conditions. As a complementary simulator to Stage, the name Gazebo was chosen as the closest structure to an outdoor stage. The name has stuck despite the fact that most users of Gazebo simulate indoor environments.
Over the years, Nate continued development of Gazebo while completing his PhD. In 2009, John Hsu, a Senior Research Engineer at Willow, integrated ROS and the PR2 into Gazebo, which has since become one the primary tools used in the ROS community. A few years later in the Spring of 2011, Willow Garage started providing financial support for the development of Gazebo. In 2012, Open Source Robotics Foundation (OSRF) spun out of Willow Garage and became the steward of the Gazebo project. After significant development effort by a team of talented individuals, OSRF used Gazebo to run the Virtual Robotics Challenge, a component in the DARPA Robotics Challenge, in July of 2013.
OSRF continues development of Gazebo with support from a diverse and active community. Stay tuned for more exciting developments related to robot simulation.