Google Summer of Code 2020: Ignition RViz
Organization: Open Source Robotics Foundation
Mentor: Alejandro Hernández Cordero
Student: Sarathkrishnan Ramesh (firstname.lastname@example.org)
Link to GSoC project: https://summerofcode.withgoogle.com/projects/#6371176131067904
Greetings to all the fellow roboticists!
I was elated on receiving the opportunity to work on developing ignition-rviz for ROS2 under the Google Summer of Code 2020 program with Open Source Robotics Foundation this summer. I would like to thank my mentor @ahcorde for his support and guidance throughout the course of the project and I am extremely grateful to Open Robotics for providing me this opportunity. I thoroughly enjoyed working on the project and it has been an amazing experience for me.
About the project
RViz is a 3D visualization tool for robots using ROS and it has undeniably been a key component of every ROS developer during the development of their robot. With the recent development in ROS2 and the refactor of Gazebo into modular libraries i.e. ignition libraries, it was the perfect time to give RViz the much deserved revamp.
Link to the project; https://github.com/ignitionrobotics/ign-rviz
Ignition RViz is built using the ignition libraries, mainly, ign-rendering and ign-gui. The application inherits its material design and easy to use user interface from the ign-gui library, therefore attaining the standards of a modern-day application. All the plugins are developed using the widgets framework provided by the GUI library. The Scene3D widget is used as the main viewport which is powered by the ign-rendering library. The rendering library offers a unified API for creating graphics while providing an abstraction for different rendering engines. This is a departure from the current implementation of RViz which uses its own rendering abstraction supporting only OGRE. By using ignition libraries, maintenance becomes much easier as it ensures propagation of any updates like bug fixes or features from the underlying libraries to ignition-rviz.
Plugins can be loaded by either display type or by topic. In the above demo, you can see the RobotModel along with its TF. The LaserScan data was visualized by loading the plugin by topic. You can undock, move around the config panel for all the plugins as well as change their background color for better visibility. The global options plugin is used to change the fixed frame.
A detailed description of the architecture of ign-rviz and display plugin system can be found in the project wiki: https://github.com/ignitionrobotics/ign-rviz/wiki
The following display plugins were developed for ign-rviz:
The following display plugins were developed:
|Global Options||Configure global options like changing fixed frame and scene background color.|
|Axes||Renders an axis at the origin of the target frame|
|Image||Displays Image received as
|LaserScan||Renders data from
|Path||Renders data from
|PointStamped||Renders data from
|Polygon||Renders data from
|Pose||Renders data from
|PoseArray||Renders data from
|RobotModel||RobotModelDisplay plugin renders robot model in the correct pose as defined by current TF transforms|
|TF||Displays the robot TF transform hierarchy|
Here we can see all the visualization plugins in action, with their config panels in the right split. The data visualized is PoseArray as red arrows, PoseStamped as Axes, PointStamped as Spheres, PolygonStamped as rotating cyan ring, and Path as the green line in the back.
This is a demo with Turtlebot3 simulation and Navigation2 in waypoint mode. The camera feed can be seen in the top left. RobotModel, LaserScan, robot footprint as Polygon and the robot plan as a Path is visualized.
Conclusion and Future plans
During the course of GSoC, I was able to achieve most of my goals and have developed some commonly used display plugins but there are still a few important ones like PointCloud & Costmap that are not yet available. Apart from adding support for the default plugins, I also have plans for developing plugins like robot teleop, plotting, and raw topic data display.
ign-rviz will be available to download as a binary in the near future. Till then if you are curious, you can try it out by building it from source. I would really appreciate any feedback from the community and will address any issues or bugs that come up.
I plan to continue to be active in the community and continue developing ign-rviz whilst contributing to ignition libraries as well as other ROS packages. I would once again like to thank my mentor @ahcorde and everyone at Open Robotics for providing me with this wonderful opportunity. It has been a great learning experience and I am looking forward to continuing to work with them.
I am Sarathkrishnan Ramesh, a final year undergrad student from Manipal Institute of Technology, Manipal, India. During my undergrad years, I was part of a research team, Project MANAS which focussed on building autonomous robots. The two core projects were building a self-driving car for Indian conditions and a UGV (which won the grand prize at Intelligent Ground Vehicle Competition 2019, Michigan, USA). These two projects marked the beginning of my journey into robotics.
Thanks and Regards,