ShawnHymel

In this episode, we deploy the trained agent to the real robot and build a web-based remote controller.

In this post, we demonstrate how to implement domain randomization with reinforcement learning (using the PPO algorithm) to balance a 2-wheel robot.

In this post, we demonstrate how to implement domain randomization with reinforcement learning (using the PPO algorithm) to balance a 2-wheel robot.

In this post, we'll show how to deploy a trained actor neural network from a PPO agent to an ESP32 robot using Arduino.

In this episode, we develop a Gymnasium environment wrapper for our MuJoCo simulation, implement a custom version of Proximal Policy Optimization (PPO), and use a technique called curriculum learning to train the robot to balance on its own.

Reinforcement Learning for Robotics is a hands-on guide to training a real robot using modern RL techniques, from simulation to hardware deployment. By the end of the series, you'll have a working remote-controlled balance bot.