Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 21 hours
Course Outline
Foundations of Robot Learning
- The role of machine learning in robotics
- Comparing supervised, unsupervised, and reinforcement learning
- RL applications in control, navigation, and manipulation
Core Concepts of Reinforcement Learning
- Markov decision processes (MDP)
- Understanding policies, value functions, and rewards
- Balancing exploration and exploitation strategies
Traditional RL Algorithms
- Q-learning and SARSA methodologies
- Monte Carlo and temporal difference learning
- Value iteration and policy iteration techniques
Advanced Deep Reinforcement Learning
- Integrating deep learning with RL (Deep Q-Networks)
- Policy gradient approaches
- Sophisticated algorithms: A3C, DDPG, and PPO
Simulation Platforms for Robotic Learning
- Leveraging OpenAI Gym and ROS 2 for simulation
- Designing bespoke environments for specific robotic tasks
- Assessing model performance and training stability
Implementing RL in Robotics
- Developing control and motion policies
- RL applications for robotic manipulation
- Multi-agent reinforcement learning in swarm robotics
Optimisation, Deployment, and Real-World Application
- Tuning hyperparameters and designing reward structures
- Bridging the gap from simulation to reality (Sim2Real)
- Deploying trained models onto physical robotic hardware
Conclusion and Future Directions
Requirements
- A solid grasp of fundamental machine learning concepts
- Proficiency in Python programming
- Knowledge of robotics and control systems
Target Audience
- Machine learning engineers
- Robotics researchers
- Developers creating intelligent robotic systems
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.
