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. .. image:: _static/arm.gif :alt: Example GIF :align: center 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*.