Robotics Operating System
Introduction
An open-source framework called ROS is used to create robotic systems. It offers a set of protocols, tools, and libraries to assist developers in building reliable & modular robot applications.
ROS and OS
An operating system is software that acts as an interface between hardware and applications. It provides a security layer by managing the scheduling of resources, including memory and processor time, through the use of scheduling algorithms and maintaining a log of various users' authority. The kernel, a low-level program that aids in hardware interface and is fundamentally the most significant component of every operating system, is nearly always present.
Because ROS presume there is an underlying operating system that will help it do its responsibilities, it is a meta operating system rather than an operating system.
What is ROS?
The open-source Robot Operating System, or ROS, framework is used to create robotic systems. With its adaptable and modular architecture, developers can use a variety of libraries, tools, and community-contributed packages to create sophisticated robot applications.
Since its initial development in 2007 at Stanford University, ROS has been a major force in the robotics community. Its sizable and engaged user community has helped to expand and improve its features and functionalities greatly.
Despite its name, ROS is not an operating system in the conventional sense. Instead, it functions as a middleware layer, providing a set of abstractions and features specifically designed for robots on top of a traditional operating system (like Linux).
ROS strongly emphasizes cooperation and reuse, which is one of its main advantages. It promotes the creation and distribution of "packages," which are reusable software components. By encapsulating particular capabilities or algorithms, these packages facilitate developers' ability to expand upon pre-existing work and take advantage of the community's collective knowledge and skills.
The distributed architecture used by ROS allows several programs, referred to as "nodes," to exchange messages with one another. Nodes can interchange data, commands, and sensor information in an interoperable and standardized way thanks to this messaging system. It encourages scalability and modularity, allowing programmers to disassemble large, complicated systems into smaller, more manageable parts that may be independently built and tested.
Moreover, ROS offers an extensive array of tools for analysis, simulation, debugging, and visualization that significantly streamline the development and debugging process. These tools include debugging tools like rqt_console for tracking and examining system log messages, simulation environments like Gazebo for testing and assessing robot behaviour, and visualization tools like RViz for viewing robot models and sensor data.
Goals of ROS
Compared to other robot software systems (OpenRTM, OPRoS, Player, YARP, Orocos, CARMEN, Orca, MOOS, Microsoft Robotics Studio), ROS serves a different function. "Create the development environment that allows robotic software developers to collaborate on a global level" is the stated mission of Robotic Open Source (ROS). In other words, rather than concentrating on the so-called robot software platform, middleware, & framework, ROS aims to maximize code reuse in robotics research and development.
The following characteristics of ROS help to support this.
1. Distributed Process: It is coded as a node, which is the smallest executable process unit. Every node functions autonomously and exchanges data methodically.
2. Package handling: Because multiple processes working toward the same objective are controlled as a package, it is easy to use, build, share, alter, and distribute.
3. Public repository: Every package is uploaded, together with a license, to the developer's favourite public repository (such as GitHub).
4. API: ROS software is made to call an API and quickly incorporate it into the code. The source code of ROS programming is comparable to that of Python and C++.
5. Multiple programming languages are supported: The ROS program's client library is compatible with several different programming languages. Popular robotics programming languages like Python, C++, and Lisp, as well as Java, C#, Lua, and Ruby, can be used with the package. In other words, you can create a ROS program using any programming language.
Why ROS?
ROS, or Robot Operating System, has grown in popularity among the robotics community for several convincing reasons. Let's examine why ROS has become the preferred framework for many roboticists and researchers.
1. Modularity and reusability: ROS promotes a modular approach to software development, with capabilities packaged into reusable components known as packages. This flexibility facilitates the development, testing, and maintenance of individual components while also allowing for the seamless integration of several software modules into a larger robotic system. ROS's vast package ecosystem enables developers to use existing solutions and expand on the work of others, saving time and effort.
2. Interoperability: ROS fosters interoperability by offering a standardized messaging system for inter-node communication. Nodes can use ROS messages, services, and topics to exchange information about sensors, data, and commands. Thanks to this standardized communication protocol, complex robotic systems with heterogeneous components are easier to construct, enabling the smooth integration of diverse hardware and software components.
3. Community and Collaboration: The ROS development and research community is sizable and vibrant. This active community develops new packages, patches bugs, and produces documentation to aid in ROS's ongoing enhancement and development. Additionally, the ROS community offers assistance through user groups, mailing lists, and forums, which makes it simpler for newbies to get started and ask for assistance when needed.
4. Tools for Visualization and Simulation: ROS offers an extensive array of tools for analysis, simulation, and visualization. Developers can see robot models, sensor data, and planning algorithms in a three-dimensional environment by using tools such as RViz. Before deploying on actual hardware, testing and evaluating robot behaviour is made easier by realistically simulating robots and their interactions with the environment in simulation environments like Gazebo. These tools support complicated robotic system troubleshooting, performance analysis, and visualization.
5. Robustness and Scalability: ROS's scalable and robust design enables the creation of intricate robotic systems. Because of its distributed architecture, ROS facilitates the deployment of numerous nodes on various machines, allowing distributed computing and parallel processing. For applications involving large-scale robot networks or real-time processing, this scalability is essential.
6. Open-Source and Cross-Platform: The ROS framework is open-source, meaning that anybody can modify and redistribute it without restriction. Because it's open source, academics and developers may work together to exchange ideas, make improvements, and expand on already-started projects. Additionally, ROS facilitates cross-platform programming, enabling programmers to collaborate with other operating systems, including Windows, Linux, and macOS.
7. Education and Learning: Learning resources and educational institutions are increasingly choosing ROS. Incorporating ROS into robotics curricula allows numerous universities and research institutions to give students practical experience in creating robotic systems. The accessibility of online courses, documentation, and tutorials facilitates the learning process for novices using ROS and integrating it into their projects.