The Resurgence of Robotic Chess: A DIY Approach
Nearly three decades have passed since Garry Kasparov’s historic defeat by IBM’s Deep Blue, a watershed moment signifying the first time a reigning world chess champion was bested by a computer. While chess engines have since advanced to the point where even basic smartphone applications can challenge grandmasters, a crucial element remained reliant on human intervention: physically manipulating the pieces. That paradigm is now evolving, thanks to innovative projects like one recently unveiled by online maker and YouTuber Joshua Stanley Robotics.
Earlier this month, Joshua Stanley Robotics showcased a self-playing chessboard constructed entirely through a do-it-yourself methodology. The project, detailed on his YouTube channel, centers around a clever application of magnetism to both detect player moves and execute the computer’s responses. This builds upon a concept explored in several prior attempts to automate the game, offering a unique and accessible take on robotic chess.
Building a Self-Automated Chess System
Joshua Stanley Robotics approached the challenge by breaking it down into three core problems: accurately registering a human player’s move, calculating the optimal computer response, and physically moving the pieces on the board. He addressed the physical manipulation aspect by custom 3D printing each chess piece, embedding a magnet within each one. The chessboard itself is constructed from a printed circuit board (PCB) featuring integrated magnetic sensors, capable of identifying piece movements and their corresponding locations.
To enact its turns, the system employs a motorized mechanism positioned beneath the board. This mechanism guides an electromagnet along the underside, activating to attract the magnet within a piece and precisely drag it to its destination square, deactivating upon arrival. This innovative approach allows for automated gameplay without the need for complex robotic arms or gripping mechanisms.
Leveraging Open-Source Intelligence
The “brain” behind this automated chessboard is the widely-used, open-source chess engine Stockfish. This choice provides Stanley with the flexibility to adjust the AI’s difficulty level on demand. He notes this is particularly useful given his own limited chess experience, stating in a project video, “To rectify this, instead of spending any time practicing or studying chess, I’m going to make a chess robot capable of beating me so thoroughly that I don’t want to play anymore.”
To bridge the gap between the physical board and Stockfish, Stanley developed a Python script to act as an intermediary. This script translates the magnetic sensor data into a digital format Stockfish can interpret, and then converts the engine’s calculated moves back into instructions for the electromagnet. Initially, he considered writing the entire control system himself, but quickly realized it was beyond his current skillset, highlighting the power of utilizing existing open-source tools.
Limitations and Commercial Alternatives
While functional, Stanley’s creation isn’t without its limitations. The drag-based movement system can struggle with certain moves, such as the knight’s jump, potentially knocking over intervening pieces. Additionally, the human player is currently responsible for removing captured pieces from the board. Despite these drawbacks, Stanley considers the project a resounding success.
“Overall, I’m really pleased with how this project turned out,” Stanley remarked. “The hidden motion of the electromagnet and the slight hum of the motors adds some suspense to every move it makes.” Several commercially available self-playing chessboards, like the $497 Miko-Chess Grand and the app-integrated Phantom, utilize similar magnetic systems, demonstrating the viability of this approach. However, Stanley’s project emphasizes the accessibility and educational value of DIY robotics and coding.
