Robot simulation is an essential tool in every roboticist's toolbox. A well-designed simulator makes it possible to rapidly test algorithms, design robots, and perform regression testing 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.
Slowly and surely we are switching Gazebo from its built-in transport library to the new Ignition Transport library based on ZeroMQ and Protobuf. The Ignition Transport library is independent of Gazebo, and designed for use in robotic and in non-robotic applications.
Recently, we have added new features to Ignition Transport including
Ignition Transport has been available in Ubuntu since Trusty, with version 1.3 scheduled for Yakkety. Gazebo 8, to be released in January 2017, will depend on Ignition Transport 1 or greater.
OSRF has internally used Ignition Transport in a number of projects, including HAPTIX and Mentor2. We believe it is ready for prime-time use, and we will be making more use of it in Gazebo and other projects.
Inertia plays an important role in simulation. An object's inertia defines how it will move and react to forces, including gravity. Incorrect inertia values can lead to strange behavior.
Gazebo has a visualization tool that helps debug inertia values. Within the Gazebo GUI, right click on a model and select View→Inertia. You should see a purple box with green axes for each link. The center of each box is aligned with the center of mass of its link. The sizes and orientations of the boxes correspond to unit-mass boxes with the same inertial behavior as their corresponding links.
A rule of thumb is to make sure the purple boxes roughly match each link in size. There are exceptions to this rule, such as an object that doesn't have uniform density.
A fire station is an active pull request to the model database.
Most recent active questions
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.
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.