Course Outline
Introduction to Robot Learning
- Overview of machine learning applications in robotics
- Distinguishing between supervised, unsupervised, and reinforcement learning
- Use cases of RL in control, navigation, and manipulation
Core Concepts of Reinforcement Learning
- Markov decision processes (MDP)
- Policy, value, and reward functions
- Balancing exploration and exploitation
Traditional RL Algorithms
- Q-learning and SARSA
- Monte Carlo and temporal difference methods
- Value iteration and policy iteration
Advanced Deep Reinforcement Learning Techniques
- Fusing deep learning with RL (Deep Q-Networks)
- Policy gradient methods
- Advanced algorithms: A3C, DDPG, and PPO
Simulation Platforms for Robot Learning
- Leveraging OpenAI Gym and ROS 2 for simulation
- Creating custom environments for specific robotic tasks
- Assessing performance metrics and training stability
Implementing RL in Robotics
- Acquiring control and motion policies
- Applying reinforcement learning to robotic manipulation
- Multi-agent reinforcement learning in swarm robotics
Optimization, Deployment, and Real-World Application
- Hyperparameter tuning and reward shaping
- Migrating learned policies from simulation to reality (Sim2Real)
- Deploying trained models on physical robotic hardware
Recap and Future Directions
Requirements
- A solid grasp of machine learning concepts
- Proficiency in Python programming
- Knowledge of robotics and control systems
Target Audience
- Machine learning engineers
- Robotics researchers
- Developers specializing in intelligent robotic systems
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
Contact us for an exact quote and to hear our latest promotions
Testimonials (2)
Supply of the materials (virtual machine) to get straight into the excersises, and the explanation of the Ros2 core. Why things work a certain way.
Arjan Bakema
Course - Autonomous Navigation & SLAM with ROS 2
its knowledge and utilization of AI for Robotics in the Future.
