KnightShift: Automated Chess Board

Abstract

The convergence of physical interaction and artificial intelligence (AI) in board games has given rise to a new generation of intelligent gaming systems. This paper presents KnightShift, an automated and voice-assisted physical chessboard system that enables seamless interaction between a human player and a computer-controlled AI opponent. The system combines sensor-based input detection, mechanical actuation, and AI processing to deliver a real-time, interactive chess-playing experience. At its core, KnightShift employs a grid of 64 reed switches organized via multiplexers to detect and update the state of the chessboard after each move. These inputs are processed using an Arduino Mega microcontroller, which communicates the current board state to a Python-based server running the Stockfish chess engine. The server analyzes the players move, calculates the AI response, and returns the optimal counter-move to the Arduino. The system then physically executes the move using a custom-built XY-plotter mechanism equipped with stepper motors and an electromagnet to pick and place chess pieces accurately. In addition to tactile move detection, KnightShift introduces a voice recognition module that allows players to make moves via speech, enhancing accessibility and user interaction. The architectural design follows a client-server model, where the Arduino acts as the client responsible for sensing and actuation, while the server handles high-level decision-making using Stockfish. KnightShift emphasizes modularity, open-source design, and affordability, making it ideal for educational use, hobbyist exploration, and research in human-computer interaction (HCI) and robotics. This paper details the hardware and software architecture, data flow, system integration, and performance evaluation of the KnightShift system. A comparative analysis with existing commercial and DIY solutions highlights KnightShifts strengths in customizability, AI integration, and physical automation. The system bridges the digital and physical worlds of chess, opening new possibilities for tangible AI applications.