We have it under Control

Theme: We Have It Under Control — this week focuses on the art and science of robot control, where mathematical feedback transforms chaotic systems into stable and predictable motion.

Example GIF

Focus

  • Understand the role of control in robotics.

  • Learn the difference between open-loop and closed-loop systems.

  • Explore feedback control and why it is essential for robots.

  • Implement PID controllers to track positions and trajectories.

Learning Flow

  1. Theory - What is control and why do robots need it? - Open-loop vs closed-loop systems. - Feedback and error correction. - Control laws: proportional (P), proportional-derivative (PD),

    and proportional-integral-derivative (PID).

    • Stability and performance in control systems.

  2. Practical / Code - Implement a simple PD controller in Python. - Extend to a PID controller for improved performance. - Test the controller on a simulated joint or mobile robot. - Visualize errors converging to zero over time.

  3. Simulation - Use Gazebo or PyBullet to simulate a robotic arm or mobile robot. - Apply your controller to track a reference trajectory. - Observe how feedback stabilizes the robot’s behavior.

  4. Assignment - Implement and test a PID controller. - Compare open-loop vs closed-loop performance. - Document results with plots of error vs time. - Push code and README to GitHub, showing:

    • Your controller implementation

    • Plots and results

    • Explanation of stability improvements

Takeaway

By the end of this week, students will understand how control transforms commands into reliable motion. They will learn that without feedback, robots drift and fail, but with control, robots execute tasks precisely.

This week gives students the tools to tame dynamics and guide robots — proving once and for all that we have it under control.