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.
During his internship with OSRF, Alex Henning developed FRCSim for the FIRST Robotics Competition (FRC). FRC is a competive high school robotics program where students build 120lb robots and compete against other robots while working on alliances. FRCSim is a set of plugins that integrates Gazebo and WPILib, the robot library used by teams, so that they can work together to allow the same code to run on FRC robots and on Gazebo simulated robots. Until recently, students on FRC teams needed access to physical robots to test their code, practice programming, and learn WPILib in just six short weeks. FRCSim currently ships with models of two actual robots and experimental support is on the way to allow teams to import their own robots into Gazebo.
Alex implemented WPILibSim in both Java and C++. He also developed Gazebo plugins for a variety of sensors and actuators, created a simplified installer for FRC teams and integrated with the WPILib Eclipse-based development tools. The current integration using the Eclipse plugins makes running the code in simulation almost identical to deploying for the real robot, the only difference is the user selects "Run in simulation" instead of "Deploy to robot". The plugin also ships with example programs that can be run and modified by students. Check out the following video for more information.
FRCSim is currently part of the closed FRC Beta and should be available to everyone in January, 2015. With its deployment, students will be given greater access to simulation environments to help them learn to program robots. It will also give them experience with simulation, which is being used more and more as part of modern robotics projects.
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.
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 every 6 months. Starting with Gazebo 4.0, releases will occur on the last week of January and July.
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.
|Measurement||Gazebo 1.9||Gazebo 2.2||Gazebo 3.0||Gazebo 4.0|
|Lines of code||186k||197k||214k||217k|
|Lines of comments||57k||63k||68k||69k|
|Test function coverage||45.7%||47.1%||41.3%||40.6%|
|Test branch coverage||32.2%||35.5%||29.2%||27.6%|
|Passing tests *||168||376||524||542|
|Failing tests *||0||0||0||0|
|gcc/clang compiler warnings||0||0||0||0|
*Performed on Ubuntu Quantal with Nvidia GPU
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.