Artificial Intelligence (AI) for Mechatronics Training in Copenhagen, Denmark

This course explores the integration of Artificial Intelligence techniques within mechatronic systems. Participants will gain a deep understanding of how AI can be applied to enhance sensing, control, decision-making, and autonomy in mechanical and electronic systems. Through practical examples, simulation tools, and real-world case studies, the course bridges the gap between AI algorithms and mechatronic applications such as robotics, autonomous systems, and smart machinery.

Introduction to AI in Mechatronics

• Role of AI in modern mechatronic systems

• Overview of machine learning, deep learning, and reinforcement learning

• Applications in robotics, drones, industrial automation

• Tools overview: Python, MATLAB, ROS

Machine Learning Basics for Mechatronics

• Supervised vs unsupervised learning

• Regression and classification models

• Data preprocessing and feature engineering for sensor data

Deep Learning and Sensor Fusion

• Neural networks, CNNs, RNNs basics

• Applications in computer vision and predictive maintenance

• Sensor fusion techniques (Kalman filter, AI-based fusion)

Reinforcement Learning and Autonomous Systems

• Introduction to reinforcement learning

• AI in motion planning and adaptive control

• Path planning and decision-making for mobile robots

System Integration and Case Studies

• Integrating AI models with real-time control systems

• Edge AI vs cloud-based AI in mechatronics

• Industry case studies: AI in robotics arms, smart factories, drones

Case Studies

Hands-on Exercises