Objectives of the training
Learn how to design intelligent robotic systems capable of interacting with their environment and collaborating with humans.Targeted audience
Robotics developers and engineers, innovation or digital transformation managers, technical trainers.Prerequisite
Basic programming skills (Python recommended). Knowledge of mathematics (linear algebra, probability). Interest in robotics and AI technologies.Trainers
Benefits for Participants
• Understand the fundamentals of artificial intelligence and its links to robotics.
• Identify and implement key algorithms used in robotic systems.
• Apply machine learning techniques to real-world cases.
• Integrate computer vision and environment recognition.
• Design AI-based human-robot collaboration scenarios.
Course architecture
Fundamentals of AI and Intelligent Robotics
Chapter 1: Introduction to Artificial Intelligence
• Definitions and types (weak vs. strong AI)
• History and developments
• Areas of application
Chapter 2: Architecture of intelligent robotic systems
• Sensors, actuators, controllers
• Perception-decision-action loop
• Embedded systems and edge computing
Workshop 1: Simulation of a mobile robot with sensors
• Use of a simulator (e.g., Webots or Gazebo)
• Sensor configuration and data visualization
Learning algorithms and computer vision
Chapter 3: Machine learning applied to robotics
• Supervised vs. unsupervised learning
• Regression, classification, clustering
• Simple neural networks
Chapter 4: Computer vision and environment recognition
• Image processing and object detection
• Facial and gesture recognition algorithms
• SLAM (Simultaneous Localization and Mapping)
Workshop 2: Object detection with OpenCV and TensorFlow
• Implementation of a recognition model
• Application to a mobile robot
Planning, decision-making, and human-robot collaboration
Chapter 5: Planning and navigation algorithms
• Search algorithms (A*, Dijkstra)
• Trajectory planning
• Obstacle avoidance
Chapter 6: Human-robot interaction and ethics
• Voice and gesture interfaces
• Reinforcement learning
• Ethical issues and safety
Workshop 3: Designing a collaborative human-robot scenario
• Setting up an assistant robot in a simulated environment
• Interaction with the user via voice or gesture commands
Pedagogical details
Type of training
Private or personalized training
If you have more than 8 people to sign up for a particular course, it can be delivered as a private session right at your offices. Contact us for more details.
Request a quotePrivate or personalized training
If you have more than 8 people to sign up for a particular course, it can be delivered as a private session right at your offices. Contact us for more details.
Request a quote