Abstract
Chess-playing robots represent a compelling integration of computer vision, robotic manipulation, and hu-man-machine interaction. This paper presents the design and implementation of an autonomous chess-playing robot capable of perceiving the game state, computing optimal moves, and physically executing piece manipulation on a standard chessboard. The proposed system combines computer vision-based board recognition, rule-constrained decision making using a chess engine, and precise motion planning for robotic actuation. This work uses a low-cost robotic system, Dobot Magician manipulator integrated with a web camera for visual recognition. The system utilizes computer vision techniques to detect and interpret the player's moves, and the robot responds with valid countermoves by physically manipulating the chess pieces. This work addresses the challenge of integrating real-time visual input with precise robotic control in a dynamic environment. As a result, a functional prototype is developed to successfully demonstrate the robot's ability to autonomously play chess game with a human opponent using vision-based inputs and precise mechanical movements.