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Simulation and Testing in Robotics: From Virtual Prototypes to Real-World Readiness
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Course Modules:
Module 1: The Role of Simulation in Robotics
Why simulate? Cost, safety, scalability, and speed
Overview of common simulators: Gazebo, Webots, PyBullet, Isaac Sim
Simulation vs. real-world discrepancies
Module 2: Setting Up Robotic Simulation Environments
Creating robots and environments in Gazebo or Webots
Using URDF and SDF files for robot description
Integrating simulation with ROS for control and data logging
Module 3: Testing Control and Navigation Systems
Simulating joint motion, sensor feedback, and movement
Testing PID control loops and trajectory execution
Verifying SLAM and localization accuracy in virtual maps
Module 4: Simulating Perception and AI Models
Testing computer vision models in varied lighting and noise
Simulating LIDAR, depth cameras, and IMUs
Injecting failure scenarios for robustness evaluation
Module 5: Test Automation and Validation
Creating automated test pipelines
Performance benchmarking, safety checks, and stress testing
Comparing simulated and expected outcomes
Module 6: Capstone Project – Simulate and Test a Robotic System
Choose a platform (Gazebo, Webots, or PyBullet)
Simulate a mobile robot, robotic arm, or drone in a realistic task
Submit logs, test plans, simulation recordings, and a project summary
Tools & Technologies Used:
ROS (Robot Operating System)
Gazebo, Webots, or PyBullet
Python for scripting and analysis
RViz for visualization
Optional: CI/CD pipelines for automated simulation tests
