[White paper] From traditional vision to AI guidance

[White paper] From traditional vision to AI guidance
Published
7.2.24

The introduction of vision systems in manufacturing has led to robots being able to react more flexibly to unforeseen situations, as the recorded and analyzed image data can be used for more precise control of robot movements.

However, standard vision systems still have limitations and do not exploit the full potential of robotics. While standard vision systems are effective in controlled or static environments, they struggle with variance, especially in lighting, angle of view, and background. Their sensitivity to certain environmental changes often leads to inefficiency and increased costs – which can even lead automation experts to avoid these systems altogether.

In an environment where adaptability and precision are key, a groundbreaking solution emerges: vision systems powered by artificial intelligence.

Benefits of AI vision-systems

Utilizing neural networks, these vision systems adapt to changes in the environment in real time and offer more flexibility and robustness. Their ability to generalize based on a few examples makes them ideal for dynamic, uncontrollable industrial settings.

AI vision-systems learn from user input how to approach a particular task that would otherwise be considered too complex to solve with conventional solutions. To gain a deeper insight into this transformative technology and its benefits, we invite you to read our white paper.  

Insights you will gain:

  • You will be able to recognize the limitations of standard vision systems in robotics and how these challenges can impact your work.  
  • You will know how AI ensures robust vision-based automation in extreme conditions.
  • You will be familiar with practical examples of AI-powered vision systems.
  • You will know how AI is paving the way for the future of robotics, and how you can stay ahead of the competition.

Download the white paper.

Using MIRAI, we have solved a challenge we could not solve with standard automation technologies. Accuracy, and performance KPIs have been reached, imprving productivity and quality.

Javier Chasco Echeverria
Engineer for Industry 4.0
Bosch Siemens Hausgeräte (BSH)
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