RL for Robotic Controls

Over the fall of 2022 I conducted research in the Newman Lab at MIT, working with a group investigating the application of reinforcement learning (RL) to robotic controls and comparing the RL solutions to human approaches. My work focused on training a model (pictured below) to stabilize an inverted pendulum using MATLAB and Simulink, approximating an ankle joint applying torque to balance a human. I also wrote a report at the end of the semester summarizing my findings.