Learn some key strategies and best practices for designing, testing, and deploying scalable robotics control software tools for complex and dynamic environments.

Take care always about your data structures and how you use time. Especially if the amount of data is big, it makes a bit of difference how you "package" them. If using C++, I can recommend C++ Optimizations Diary of Davide Faconti to learn some simple tricks that can easily lead to 20%+ increase of code performance.

How can you ensure your robotics control software tools scale for large applications?

If you are a control engineer working on robotics applications, you know how challenging it can be to design, test, and deploy software tools that can handle complex and dynamic environments. You also know how important it is to ensure that your tools can scale for large applications, such as industrial automation, autonomous vehicles, or service robots. How can you achieve this goal without compromising performance, reliability, or safety? In this article, we will explore some key strategies and best practices that can help you create scalable robotics control software tools.

1 Modularize your code

One of the first steps to ensure scalability is to modularize your code, that is, to divide it into smaller and independent units that perform specific functions. This way, you can reuse your code across different applications, reduce complexity and redundancy, and facilitate maintenance and debugging. Modularization also enables you to adopt a layered architecture, where you separate your control logic from your hardware interface, your communication protocols, and your user interface. This allows you to abstract the details of each layer and focus on the functionality and interaction of each module.

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Dr.-Ing. Denis Stogl

Owner & CEO @ Stogl Robotics | Automation and Robotics Integration Expert
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Making your code more modular might lead to even more overhead in large applications. Another disadvantage of modular code is that the individual modules get so abstracted that they are hard to understand and use in the long term. Therefore, my approach is to make modules of components known as common knowledge in control theory, and after that, those are combined into specific solutions that an application needs. This makes the code more explicit, and easier to read and maintain.

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2 Use standard frameworks and libraries

Another strategy to ensure scalability is to use standard frameworks and libraries that provide common and proven functionalities for robotics control software development. For example, you can use the Robot Operating System (ROS) framework, which offers a set of tools, libraries, and conventions for creating and running robotics applications. ROS supports multiple languages, platforms, and hardware devices, and allows you to communicate and integrate with other ROS-based applications. You can also use libraries such as OpenCV, Eigen, or Boost, which provide efficient and reliable implementations of algorithms and data structures for computer vision, linear algebra, or general programming.

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Dr.-Ing. Denis Stogl

Owner & CEO @ Stogl Robotics | Automation and Robotics Integration Expert
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This is the case. The wheel is invented almost most of the time somewhere. Maybe is it not perfectly round, but you can then polish it out for your needs. Thinking in terms of ROS or ROS 2 keep in mind to use libraries made specially for control, like ros_control or ros2_control. They are additionally optimized for realtime performance.

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3 Optimize your algorithms and data structures

A third strategy to ensure scalability is to optimize your algorithms and data structures, that is, to choose the most suitable and efficient methods and representations for your problem domain and your application requirements. For example, you can use algorithms that reduce the computational complexity and memory usage of your control software, such as recursive or iterative methods, dynamic programming, or approximation techniques. You can also use data structures that simplify the manipulation and storage of your data, such as arrays, vectors, matrices, lists, or maps.

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Dr.-Ing. Denis Stogl

Owner & CEO @ Stogl Robotics | Automation and Robotics Integration Expert
Report contribution
Take care always about your data structures and how you use time. Especially if the amount of data is big, it makes a bit of difference how you "package" them. If using C++, I can recommend C++ Optimizations Diary of Davide Faconti to learn some simple tricks that can easily lead to 20%+ increase of code performance.

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4 Test and validate your software

A fourth strategy to ensure scalability is to test and validate your software, that is, to verify that your software behaves as expected and meets the specifications and constraints of your application. For example, you can use unit testing, integration testing, and system testing to check the functionality, performance, and reliability of your software modules, components, and systems. You can also use simulation tools, such as Gazebo, Matlab, or Simulink, to model and analyze your software in realistic and controlled scenarios, before deploying it to the real hardware.

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5 Update and document your software

A fifth strategy to ensure scalability is to update and document your software, that is, to keep your software current and consistent with the changes and improvements of your application. For example, you can use version control tools, such as Git, SVN, or Mercurial, to track and manage the revisions and modifications of your software code. You can also use documentation tools, such as Doxygen, Sphinx, or Javadoc, to generate and maintain the documentation of your software code, such as comments, descriptions, or diagrams.

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