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.
Gazebo 6.x and 5.x have reached the end of their lives. We will continue to answer questions about these versions, but we will stop fixing bugs.
We are proud to announce the release of Gazebo 8. This version of Gazebo has short term support with an end-of-life on January 15, 2019.
A major API change comes with Gazebo8. This API change centers around the transition from Gazebo's internal math library to Ignition Math. Please refer to the changelog and migration guide to help your transition.
The ability to dynamically and programmatically add visual elements to Gazebo has been added through a visual marker interface. Visual markers can consist of simple shapes, lines, triangles, and text. Additional features associated with visual markers can be found through the gz marker -h command line tool. A C++ example demonstrates how to manipulate visual markers from a stand-alone application.
We continually strive to improve Gazebo's user experience and offer features that benefit a wide audience. To this end, a feature rich plotting utility has been integrated with Gazebo. This utility supports plotting data from topics, models, and simulation parameters. Multiple plots can be created, and data can be exported to CSV or PDF files. Try inserting a model, such as the Double Pendulum, and press ctrl-p.
Following the same rationale as the plotting utility, we are pleased to announce the integration of video recording in Gazebo 8. Simply select the camera icon on the right hand side of the tool bar to start recording into an MP4, AVI, or OGV file. Select the icon again to stop recording and save the video file.
Enjoy the new release, and thanks for all the contributions,
OSRF Development Team
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.
Use CloudSim to run Gazebo on Amazon, Softlayer, or your own OpenStack instance.
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.
Still need help? Send a message to the gazebosim mailing list.
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 3.0+ 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|
|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.