The official CODESYS ROS 2 library is not the only path. Consider these alternatives for specific use cases:
DDS is powerful but complex. Default settings may cause:
If you'd like, I can also provide a sequence diagram of the data flow or a pseudo‑implementation of one of the function blocks.
Integrating CODESYS with ROS 2 bridges the gap between high-reliability industrial automation (PLCs) and advanced robotic software. While CODESYS manages deterministic real-time tasks like motor control and safety, ROS 2 provides high-level capabilities like SLAM, AI, and path planning. Integration Strategies
There is no single "native" ROS 2 driver for CODESYS, but several established methods exist: micro-ROS - Putting ROS 2 onto Microcontrollers - FIWARE
Integrating (Robot Operating System 2) creates a powerful hybrid architecture that combines the deterministic, real-time control of industrial PLCs with the advanced perception and path-planning
capabilities of modern robotics frameworks. This setup is increasingly popular in Industry 4.0 for building flexible, robust automation systems. Core Architecture & Communication
The primary challenge is bridging the gap between the IEC 61131-3 languages used in CODESYS and the publisher/subscriber messaging model of ROS 2. Shared Memory Bridge
: High-speed communication is often achieved via shared memory. A ROS 2 node reads and writes data to a specific memory location that the CODESYS runtime can also access, enabling extremely low-latency data exchange. ROBIN Project codesys ros2
: This open-source bridge (originally for ROS but adaptable for ROS 2) maps CODESYS variables directly to ROS topics using a dedicated library and a ROS node. Industrial Protocols : Alternatives include using Modbus TCP
. While common, these often have higher latency compared to native shared memory implementations. Key Benefits Reliability
: PLCs like CODESYS are designed for 24/7 industrial reliability and handle low-level hardware communication (e.g., motor drives, sensors) more robustly than standard ROS 2 drivers. High-Level Intelligence
: ROS 2 provides ready-to-use libraries for SLAM, navigation, and computer vision that are not natively available in traditional PLC environments. Developer Accessibility
: It allows automation technicians skilled in IEC 61131-3 to manage robot functions without needing deep knowledge of C++ or Python. Comparison: ROS 2 vs. CODESYS Getting Started with ROS 2
Integrating CODESYS with ROS 2 allows you to combine the deterministic hardware control of industrial PLCs with the advanced motion planning and perception capabilities of the Robot Operating System. 🚀 Direct Integration Methods
Shared Memory Bridge (Recommended for High Speed): Use the ROBIN project (ScalABLE40/robin) for high-performance data exchange on the same hardware (e.g., Raspberry Pi, Beaglebone).
OPC UA Bridge: Set up an OPC UA Server in CODESYS and use a ROS 2 node as an OPC UA Client with libraries like asyncua (Python) or open62541 (C++). The official CODESYS ROS 2 library is not the only path
MQTT Messaging: Use the CODESYS MQTT library to publish PLC variables to a broker and subscribe to them via a ros2_mqtt bridge for non-real-time tasks.
Micro-ROS Agent: For microcontrollers or lightweight PLCs, run a micro-ROS node directly on the target hardware to communicate with the ROS 2 Global Data Space. 🛠️ Strategic Setup: Why use both?
Integrating CODESYS with ROS2 bridges the gap between high-level robotic decision-making and robust industrial real-time control. While ROS2 excels at perception and complex path planning, CODESYS provides the deterministic communication needed for industrial hardware. Bridging the Industrial Gap
Combining these two systems creates a powerful architecture where:
CODESYS handles low-level hardware communication (like EtherCAT or CANopen) to ensure reliable, real-time machine safety and motion.
ROS2 manages high-level logic, SLAM, and visualization through its distributed node system. Popular Integration Methods
Because CODESYS and ROS2 don't naturally "speak" the same language, developers typically use one of these bridges:
ROS-Bridge & WebSockets: A common approach involves using a ROS-Bridge client within CODESYS that connects via WebSockets to the ROS network. If you'd like, I can also provide a
Intermediate Protocols: Using Modbus or OPC UA as an intermediary layer. For example, a Python script in the ROS2 workspace can act as a bridge, reading data from CODESYS via Modbus and publishing it to a ROS2 topic.
Direct Driver Development: Writing custom C++ drivers that handle the hardware mapping in a way that remains compatible with ROS2's communication. Getting Started with ROS2 Topics
If you are new to the ROS2 side of the equation, the core communication revolves around topics—anonymous channels where nodes publish or subscribe to data:
Define your data: Use standard messages like geometry_msgs/msg/Twist for motion or create custom messages for specific industrial signals.
Launch a Bridge Node: This node will take your PLC data and use ros2 topic pub to push it into the ROS network.
Visualize: Use tools like rqt_graph or the MATLAB Message Viewer to confirm your CODESYS data is successfully streaming across topics.
Are you planning to use a Raspberry Pi as your industrial gateway, or are you working with a specific PLC hardware like Beckhoff or Wago? What is a ROS2 Topic? - ROS2 Tutorial 6