Connect Four Robot: Reinforcement Learning on Embedded Hardware

Mon, 16 Oct 2023 11:13:50 +0100

The Connect Four robot is a physical demonstrator for reinforcement learning. It was originally developed as a master’s project in the EIM program (Electrical Engineering and Information Technology) by the students Alexander Bernhardt, Christian Bernhardt, Raphael Carli and Manuel Reichelt.

In addition to a DQN agent, a Monte Carlo Tree Search (MCTS) agent and AlphaZero were implemented. All algorithms were parameterized to run in real time on a Raspberry Pi 4. Different difficulty levels can be selected via a touch display. At the highest level, winning against the AI is nearly impossible.

Alongside the software, an open-source robot arm was built with a 3D printer, a sensor system was set up on a real game board, and a magazine was designed from which the robot arm picks up the game pieces.

The robot attracted the interest of local media, who visited the project at HTWG in autumn 2023. A Regio TV report about the project is available in the media library: (in German)

An article was also published in the Südkurier: (in German)

Current work

The setup is currently being extended with a Dobot Magician E6, a six-axis collaborative robot arm.

Robotics | Christopher Knievel

Connect Four Robot: Reinforcement Learning on Embedded Hardware

Current work