Thanks to broad support in the robotics community and the availability of numerous open source packages, vision components can be quickly integrated and individual solutions realized. ROS and ROS 2 offer a high degree of flexibility and scalability, particularly in research and development environments and in prototyping.

Comparing the most important manufacturer-specific interfaces

The table provides an overview of the most important properties and application areas of the respective robotic interfaces for integrating machine vision into robotic applications in industrial environments.

Direct communication between vision system and robot controller

With this type of integration, data such as pick positions, quality features, or status information can be transmitted without detours to the robot controller and processed directly in the robot program.

By extending the command set or adapting parameters, tasks such as dynamically transferring gripping points, controlling test sequences, or flexibly adapting to changing production conditions can be implemented efficiently. Direct integration ensures short reaction times and high process reliability. It also opens up new possibilities for intelligent automation in robotics.

Tips for successful integration

Successfully integrating machine vision into robotics applications requires careful planning and attention to technical details. The following tips will help you overcome typical challenges and implement an efficient, reliable solution:

• Select the interface that best suits your robot platform and your application requirements (e.g. REST API, OPC UA, manufacturer-specific plugins).

• Check the compatibility of the camera, vision software, and robot controller early on in the project.

• Use existing sample codes and templates for fast and error-free integration.

• Make sure that the network and communication parameters are configured correctly to ensure stable data transmission.

• Allow sufficient time for testing and validation of the overall solution, especially for complex or safety-critical applications.

• Document interfaces and processes clearly to facilitate maintenance and extensions.

Summary

The successful integration of machine vision in robotics applications opens up new possibilities for precise, flexible, and efficient automation solutions. Various interfaces, such as REST API, OPC UA, ROS, gRPC, or manufacturer-specific plugins, enable seamless communication between machine vision systems and robot controllers.

3D vision offers decisive advantages, such as reliable object recognition and dynamic adaptation to complex environments. Real-life examples, such as pick-and-place, bin picking, and quality control, show how efficiently modern vision solutions can be used in robotics.

Selecting the right interface and carefully planning the integration are crucial for the success of the project. This allows image processing and robotics to be optimally combined to meet the requirements of modern production environments.