Build a Physical PPO Cart-Pole Agent

Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.

Most reinforcement learning stays in simulation. This kit bridges the gap by training a Proximal Policy Optimization (PPO) agent directly on a physical cart-pole system. You'll mount a servo-driven cart, read pendulum angle from the MPU6050 IMU at 200 Hz, and watch the agent learn to balance in under an hour of real-time training-all on a Raspberry Pi 5 with onboard NVMe acceleration.

What You'll Build

A real-world cart-pole balancing agent that learns optimal control policies from live sensor data. The build involves a servo-actuated cart moving along a linear rail, with the IMU measuring pole angle in real time. The Pi 5 runs PPO training loops, saves checkpoints to NVMe, and deploys the trained policy for persistent, low-latency balancing-no cloud needed.

What You'll Learn

• Implementing PPO reinforcement learning on a physical system with continuous state and action spaces
• Interfacing a 6-axis IMU (MPU6050) with Raspberry Pi 5 over I2C at 200?Hz update rate
• Controlling a servo motor for real-time cart actuation and understanding latency impacts in RL
• Deploying a trained RL policy on the edge and managing real-world noise, safety, and convergence

Kit Contents

Why Buy This Kit Instead of Sourcing Parts Separately

Who This Kit Is For

This kit is designed for advanced makers, undergraduate ECE/CS students tackling reinforcement learning hardware projects, and researchers prototyping sim-to-real algorithms. It fits B.Tech final-year projects, NIT/IIT research labs exploring edge AI, and Smart India Hackathon teams building autonomous balancing demonstrators. If you've worked with Raspberry Pi and Python before and want to escape simulation, this kit delivers a complete RL-on-hardware stack.

Built and Backed by Compoden

Every Compoden kit ships with an AI build companion trained on this exact project - accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.