With the warming of domestic robots in the past two years, autonomous positioning and navigation technology as the first step of intelligent robotization has been attracting attention in the industry. In order to achieve this function, many manufacturers choose to use the robot operating system ROS (Robot Operation System), today we will talk about the ROS system.

1. What is ROS?

The ROS system originated in 2007, and Stanford University's artificial intelligence laboratory and robotics company Willow Garage developed the prototype of ROS for its Personal Robots Program. After 2008, the further development of ROS was promoted by Willow Garage. After 2012, the ROS team became independent from WillowGarage and became the non-profit organization of the Open Source Robotics Foundation (OSRF), responsible for maintaining and updating ROS and providing support and open source tools for the robot community.

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ROS releases a version every year, and the ROS versions currently being maintained include indigo, jade, kinetic, and some earlier versions have now stopped maintenance. ROS relies on the Linux kernel, so whenever the Ubuntu version changes, the dependencies of different versions of ROS will change accordingly.

2. Characteristics and advantages of ROS

ROS is called the robot operating system. In fact, ROS acts as the communication middleware, that is, based on the existing operating system, a complete set of implementation framework for the robot system is built. ROS also provides a set of utilities and software libraries for maintaining, building, writing, and executing software code that can be used on multiple computing platforms.

It is worth mentioning that the designers of ROS consider the development language used by each developer differently, so the development language of ROS is independent and supports various development languages ​​such as C++ and Python. Therefore, in addition to the officially provided feature packs, ROS also aggregates a large number of open source feature packs implemented by developers around the world. For example, SLAMTEC has released the ROS feature package rplidar_ros for its self-developed lidar RPLIDAR. These open source feature packs together with ROS form a powerful open source ecosystem.

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