How can you choose the right programming language for an industrial robot?

Hardware compatibility is extremely important in choosing the right programming language of an industrial robot. Each industrial robot manufacturer has proprietary software (e.g.) Inform commands for YASKAWA robots, Kuka Robot Language (KRL) for Kuka robots, RAPID for ABB robots, TP programming language for FANUC robots. Due to the closed language architectures, recently many startups started using open software like Robot Operating System (ROS) and python to calculate the joint angles of industrial robot.

Absolutely, hardware compatibility is crucial when selecting a programming language for industrial robots. Ensuring that the language aligns with the specifications of the robot's controller, processor, memory, and interfaces is essential for seamless integration and efficient operation. Taking into account factors like Microprocessors or Microcontroller presence can further refine the language choice to best suit the specific needs and capabilities of the robot system.

In selecting a programming language for robotic system development, meticulous consideration of compatibility, project requirements, and efficiency is crucial. Define system needs, ensuring compatibility with hardware and OS. Opt for C or C++ for real-time processing, Python for versatility and readability. Engage an active community for support. Explore frameworks like ROS and simulation tools like Gazebo. Prioritize scalability and consider Python with TensorFlow or PyTorch for AI/ML integration. A judicious choice aligns with current and future robotic system needs, ensuring effective development.

In robotic development, software functionality is crucial for controlling the robot's behavior. The software stack includes firmware for low-level hardware control, middleware like ROS for communication, perception algorithms for sensor data processing, motion planning for path generation, and control algorithms for precise movements. High-level logic, often in Python, manages decision-making and task planning. Simulation tools test algorithms before deployment. This software orchestrates hardware components, allowing the robot to perceive, plan, and execute tasks autonomously or under human guidance.

In the realm of robotic development, the application domain delineates the specific context and purpose of a robot's deployment. Whether in manufacturing, healthcare, logistics, or exploration, the application domain shapes the design and functionality of the robotic system. Industrial robots excel in tasks like assembly and welding, while medical robots aid in surgeries or patient care. Autonomous vehicles navigate the transportation domain, and exploration robots venture into hazardous environments. Understanding the application domain is pivotal, influencing sensor configurations, control algorithms, and interaction interfaces to ensure the robot meets the targeted needs efficiently and safely.

When selecting a programming language for industrial robots, consider environment integration to ensure seamless communication with existing systems. Evaluate compatibility with control software and hardware, such as PLCs or HMIs. Choose a language that supports industry standards like OPC UA for interoperability. Additionally, assess support for real-time performance, safety features, and maintenance requirements. Prioritize languages with robust libraries for robotics, such as C++, Python, or ROS, to streamline development and enhance flexibility.

An industrial robot's programming language depends on its tasks, compatibility with existing systems, ease of programming, library availability, and development team competence. RPLs, ST, C/C++, Python, ROS, Blockly, and Scratch are popular programming languages. RPLs are specific to robot brands, ST is high-level, C/C++ is good for complex robot control algorithms, Python is simple, readable, and has a large library for computer vision and machine learning, ROS is a framework for robot software, and Blockly or Scratch are beginner-friendly visual programming languages. Using libraries, frameworks, and best practices streamlines development and ensures project success.

When I was starting my field in robotics, it was hard for me to choose the programming language for robotics. After searching for 2 to 3 years, I have understood the simple rule that the developer should think about the functionality, not the hardware. E.g. If you're working on an application like analysing a system, then python is preferable as it has rich libraries, but on the other hand, if you want speed, C or C++ is recommended, etc.