Cross-cutting

Artificial Intelligence and Mechatronics

AI Academy 40 hours

Introduction

The course Artificial Intelligence and Mechatronics invites you to immerse yourself in two of the the most dynamic and promising fields of the 21st century. At present, the integration of artificial intelligence into mechatronic systems is revolutionising industries, from the automotive sector to robotics, with a a steadily growing demand for labour. During the course, you will explore the possibilities of the AI and its application in mechatronics, you’ll understand the expert systems and the fuzzy logic, and you’ll get to know genetic algorithms and neural networks. You will develop skills to to create innovative models and efficient solutions, equipping you to cope with current and future challenges. Our online training ensures flexibility and access to the latest technological trends, preparing you to excel in a a competitive and expanding market. Join this a journey into the future of technology.

Objectives

  • Understanding artificial intelligence and its application in mechatronics.

  • Analysing the components and structure of an expert system.

  • Implement fuzzy logic in automated decision-making.

  • Designing route-finding algorithms using advanced methods.

  • Apply genetic algorithms to solve complex problems.

  • Exploring neural networks and how they work in smart systems.

  • Developing skills to create expert systems that deal with uncertainty.

Table of Contents

TEACHING UNIT 1. MECHATRONICS AND ARTIFICIAL INTELLIGENCE: POSSIBILITIES
Artificial Intelligence: an introduction
Intelligence in living beings
Artificial Intelligence
Areas of application
The field of mechatronics
The possibilities of Artificial Intelligence
Mechatronics and Artificial Intelligence

TEACHING UNIT 2. EXPERT SYSTEMS
What is a polygon expert system?
Structure of an expert system
Inference: types
Development of expert systems

TEACHING UNIT 3. FUZZY LOGIC
An Introduction to Fuzzy Logic
Fuzzy sets and degrees of membership
Operators on fuzzy sets
Creating rules
Fuzzification and defuzzification

TEACHING UNIT 4. ROUTE SEARCH
An Introduction to Route Planning
Paths and graphs
Exhaustive and "intelligent" route-finding algorithms"
Implementation

TEACHING UNIT 5. GENETIC ALGORITHMS
What are genetic algorithms?
Biological and artificial evolution
Election of representatives
Assessment, selection and survival
Reproduction: crossover and mutation
Areas of application

TEACHING UNIT 6. NEURAL NETWORKS
An Introduction to Neural Networks
Biological origin
The formal neuron
Perceptron
Feed-forward networks
Learning
Other networks

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