Design and Implementation of a Computer Vision System for an Autonomous Chess-Playing Robot

Abstract

This work describes a mechatronic system composed by a robot arm that can play chess autonomously. The system is based on an industrial-grade robot manipulator, a computer vision system, and an open source chess engine. Classification algorithms were implemented in order to detect whether a given chessboard square is occupied, and in that case, if the piece is black or white. Such algorithms were compared in terms of their complexity of implementation, execution time and accuracy of predictions. To achieve an uniform illumination of the chessboard, a theoretical model of an LED illuminance curve was used to find the best orientation for each diode using a genetic algorithm. Both the support base for the LEDs and the chess pieces were made using a 3D printer. This implementation demonstrates the capabilities of the proposed vision-based system, whose complexity can be increased in the future for a number of applications.

Playing Checkers with an Intelligent and Collaborative Robotic System

“…Differently, piece position and color are often more difficult to obtain. There are different solutions to reduce this issue, such as using colored pieces (they are normally black and white) in order to increase the contrast with squares (also usually black and white) [15,16], adopting a dedicated lighting system [17], or implementing strategies to compensate for distortions and lighting variations [13,18].…”

Design and Construction of a Cost-Effective Didactic Robotic Arm for Playing Chess, Using an Artificial Vision System

“…Since then, many chess engines have been developed, and simultaneously it has become easier to develop mechanical robots [6,7]. The chess game is an excellent application that works as a test bed for the implementation of autonomous robotic systems, as it requires solutions for perception, manipulation, and human-robot interactions for a well-structured problem [8][9][10][11][12].…”