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.
This past month we have started a development push on our web-technologies. CloudSim, a tool used to provision and manage cloud-based simulations, and PropShop are getting a reboot. Stay tuned over the coming months for updates.
We spent a week on a usability sprint, with the goal of putting ourselves in the shoes of first-time simulation users. The sprint utilized the FIRST 2016 competition environment. Two teams were tasked with constructing three robots using Gazebo and ROS. At the end of the week we generated and long list of usability issues, which we are now busy resolving.
We had a bit of fun at the end of the sprint, in the form of a live competition. Both teams setup in the OSRF cafe, and connected to Gazebo running the FRC 2016 environment. Check out the video below for a quick take on the robots we created.
This month's tip is about improving simulation performance.
Triangle mesh collisions are both CPU intensive and error prone. Use mesh objects for visuals, and simple shapes for collisions.
Try to reduce the number of joints, including fixed joints, in models. Each joint introduces a constraint that the physics solver must compute.
Meshes may contain screws and internal structures that are not useful in simulation, and only slow down rendering.Open your meshes in a 3D modeling tool, such as Blender, and remove or reduce the number of triangles.
Check sensor update rates and resolutions. For example, ask yourself if you need an HD camera in simulation.
We need your help to squash bugs! Please visit our issue trackers to get started.
Gazebo Issue #1058: Update GearBox Joint Definition
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.