Supervised learning is a subcategory of machine learning. In this context, learning refers to the ability of artificial intelligence to reproduce regularities. In supervised learning, algorithms are able to learn from historical data and apply it to unknown inputs to determine the correct outputs. The aim is to generate a precise mapping function that allows the algorithm to predict a solution as soon as a new input is provided. Supervised learning is often used in applications such as image and speech recognition or classification.
fischertechnik’s Quality Control with AI model makes theoretical content come alive by presenting the functions of supervised learning in a tangible way. By understanding how supervised learning works, young users learn how intelligent machines are used in industry, removing the barriers to this multi-layered technology. The model is suitable as a training, simulation and demonstration model for education, industry and research.
fischertechnik Quality Control with AI comes with workpieces in different colours. These workpieces are equipped with three processing characteristics and various error patterns. They are scanned by the camera before being classified and sorted according to their colour, features and error pattern through supervised learning.
The AI is implemented with machine learning in Tensorflow, which involves training an artificial neural network with image data. The trained AI is carried out on the fischertechnik TXT 4.0 Controller, which offers suitable wireless interfaces for various applications. The model’s sequence control is implemented through the ROBO Pro Coding programming environment and Python.
Users can also programme their own AI applications. Training is carried out through an algorithm based on Python, a universal, high-level programming language. A sample project is available for training purposes.
“We want to fundamentally encourage problem-solving and problem-oriented learning with this product”, says fischertechnik’s Managing Director Thomas Bußhart, explaining the idea behind the innovation. Strengthening technology skills and the confidence to apply them is the main objective. “In doing so, we want to remove the entry barriers to supervised learning”.
Swarm Lab, a laboratory and competence centre at the Cooperative State University in Mosbach / Campus Bad Mergentheim, focuses on researching artificial intelligence specialising in swarm intelligence and deep learning. Campus Bad Mergentheim is part of the Mosbach Cooperative State University, which focuses on teaching and researching artificial intelligence. Prof Carsten Müller researches the application of swarm intelligence at the campus, particularly the adoption of algorithms inspired by nature and their fields of application in logistics. He uses fischertechnik’s powerful Quality Control with AI technology while teaching and researching artificial intelligence focused on machine vision. “The interaction between the software and physical elements creates an understanding of artificial intelligence”, Carsten Müller states, explaining his decision to opt for fischertechnik. Understanding complex supervised learning processes illustrates how intelligent machines work in the industry. “The fischertechnik model is powerful, smart and intuitive to use, making it ideal for learning about artificial intelligence”, Carsten Müller explains.
