Course: Training Humanoid Robots in Simulated Environments – From Theory to Practice

Course Description

This intensive course will guide you step by step through the process of training and testing humanoid robots using the most advanced simulation environments available today. By the end of the course, you will have hands-on experience in setting up, running, and optimizing robotic simulations for AI development, reinforcement learning, and real-world deployment.

We will cover three major robotic simulation platforms:

  • Isaac Sim / Isaac Lab (NVIDIA) – best for high-fidelity physics and AI integration.
  • Gazebo – widely used in industrial robotics and ROS ecosystems.
  • Webots – a user-friendly platform for education and research.

Who Is This Course For?

  • Engineers and developers interested in robotic simulation and AI training.
  • Researchers and students looking to understand sim-to-real transfer.
  • Enthusiasts aiming to build and simulate humanoid robot behaviors.
  • Professionals seeking to integrate ROS-based robotic systems.

Course Modules

Module 1: Introduction to Robotic Simulation

  • Overview of robotic simulation platforms.
  • Importance of sim-to-real transfer in robotics.
  • Key differences between Isaac Sim, Gazebo, and Webots.

Module 2: Isaac Sim – AI and Reinforcement Learning for Humanoids

  • Setting up Isaac Sim and understanding Omniverse.
  • Implementing PhysX-based physics for realistic humanoid motion.
  • AI integration using Isaac Gym and reinforcement learning (RL).
  • Optimizing performance for GPU-accelerated simulations.

Module 3: Gazebo – ROS Integration for Industrial Robotics

  • Understanding ODE, Bullet, and Dart physics engines.
  • Creating and running humanoid robot models in Gazebo.
  • Integrating ROS 1 & ROS 2 for real-world robotic applications.
  • Running large-scale simulations for multi-robot environments.

Module 4: Webots – A Beginner-Friendly Approach to Robotic Simulation

  • Exploring Webots’ intuitive interface and built-in robot models.
  • Writing robotic control programs in Python and C++.
  • Simulating human-robot interactions in different environments.
  • Exporting Webots scenarios to VR-based robotics applications.

Module 5: Sim-to-Real Transfer – Bridging the Gap

  • Challenges in transferring simulations to real-world robots.
  • Best practices for sensor calibration and motion control.
  • Case studies of successful humanoid robot training.

Module 6: Hands-on Project – Training Your Own Humanoid Robot

  • Choose your preferred simulation platform (Isaac Sim, Gazebo, or Webots).
  • Design and train a humanoid robot for a specific task (e.g., object manipulation, walking).
  • Optimize physics parameters and analyze performance.
  • Present your project and receive feedback from experts.

Key Takeaways

✅ Learn how to simulate humanoid robots using state-of-the-art software.
✅ Gain hands-on experience with Isaac Sim, Gazebo, and Webots.
✅ Develop AI-based humanoid robot behaviors using reinforcement learning.
✅ Understand ROS integration and industrial robotic applications.
✅ Build and optimize your own robotic simulation project.

🚀 Are you ready to master humanoid robot training? Join the course now!