The main intention behind building the ROS framework is to become a generic software framework for robots. Even though there was robotics research happening before ROS, most of the software was exclusive to their own robots. Their software may be open source, but it is very difficult to reuse.
Compared to existing robotic frameworks, ROS is outperforming in the following aspects:
- Collaborative development: As we've already discussed, ROS is open source and free to use for industries and research. Developers can expand the functionalities of ROS by adding packages. Almost all ROS packages work on a hardware abstraction layer, so it can be reused easily for other robots. So, if one university is good in mobile navigation and another is good in robotic manipulators, they can contribute that to the ROS community and other developers can reuse their packages and build new applications.
- Language support: The ROS communication framework can be easily implemented in any modern programming language. It already supports popular languages such as C++, Python, and Lisp, and it has experimental libraries for Java and Lua.
- Library integration: ROS has an interface to many third-party robotics libraries, such as Open Source Computer Vision (OpenCV), Point Cloud Library (PCL), Open-NI, Open-Rave, and Orocos. Developers can work with any of these libraries without much hassle.
- Simulator integration: ROS also has ties to open source simulators such as Gazebo and has a good interface with proprietary simulators such as Webots and V-REP.
- Code testing: ROS offers an inbuilt testing framework called rostest to check code quality and bugs.
- Scalability: The ROS framework is designed to be scalable. We can perform heavy computation tasks with robots using ROS, which can either be placed on the cloud or on heterogeneous clusters.
- Customizability: As we have already discussed, ROS is completely open source and free, so we can customize this framework as per the robot's requirements. If we only want to work with the ROS messaging platform, we can remove all of the other components and use only that. We can even customize ROS for a specific robot for better performance.
- Community: ROS is a community-driven project, and it is mainly led by OSRF. The large community support is a great plus for ROS and means we can easily start robotics application development.
The following are the URLs of libraries and simulators that can be integrated with ROS:
- Open-CV: http://wiki.ros.org/vision_opencv
- PCL: http://wiki.ros.org/pcl_ros
- Open-NI: http://wiki.ros.org/openni_launch
- Open-Rave: http://openrave.org/
- Orocos: http://www.orocos.org/
- V-REP: http://www.coppeliarobotics.com/
Let's go through some of the basic concepts of ROS; these can help you get started with ROS projects.