In this project, you will learn about and implement an optimal robot control algorithm for simple robotic systems, such as a cart-pole or 2D quadcopter. We will begin with a brief survey of state-of-the-art control methods, develop a strong understanding of the underlying physics, and then implement the control algorithms in a Python simulator to validate our methods. This will include a guided exploration of advanced controls techniques - Python experience preferred.

Optimal Control Methods for Simple Robot Systems

Given the extensive variations in quadruped robot morphologies in both research and commercial platforms (think Boston Dynamics Spot vs ETH Zurich ANYmal), let's explore how the different hardware designs affect performance and types of tasks. This project will involve a review of the hardware design decisions from a selection of some of the most influential quadruped platforms and an analysis on how different configurations affect the robot dynamics.