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An Intelligent System-Based Strategic Plan for a Humanoid Robot Playing the Game of Dominoes
Plan estratégico basado en sistemas inteligentes para el juego de dominó por parte de un robot humanoide
DOI:
https://doi.org/10.15446/ing.investig.108904Keywords:
computer vision, decision tree, dominoes, board games, forward kinematics, human robot interaction, image processing, intelligent system, NAO robot, robotics (en)visión por computadora, árbol de decisión, dominó, juegos de mesa, cinemática inversa, interacción humano-robot, procesamiento de imágenes, sistema inteligente, robot NAO, robótica (es)
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The application of intelligent systems in humanoid robots provides research and development alternatives, as is the case with human-robot interaction. This paper focuses on the design and implementation of an intelligent system in the NAO robot to plan and execute moves in the board game known as dominoes. This system uses the NAO robot’s vision to determine the distribution of tiles on the board, as well as those available in hand. The appropriate moves are planned using a computational intelligence technique, and a kinematics model executes them. The results show that the vision system has an average error of 5.62%, in addition to 3.37% for the decision-making system and 7.87% for the kinematics of the robot. This leads to the NAO robot being capable of making successful plays through the proposed system, with an average effectiveness of 83.15%.
La aplicación de sistemas inteligentes en robots humanoides brinda alternativas de investigación y desarrollo, como es el caso de la interacción humano-robot. Este trabajo se enfoca en el diseño e implementación de un sistema inteligente en el robot NAO para planificar y ejecutar movimientos en el juego de mesa conocido como dominó. Este sistema utiliza el sistema de visión del robot NAO para determinar la distribución de fichas en el tablero y de las disponibles en la mano. Los movimientos adecuados se calculan mediante una técnica de inteligencia computacional, y un modelo de cinemática los ejecuta. Los resultados muestran que el sistema de visión tiene un error promedio del 5.62 %, ası como del 3.37 % para el sistema de decisión y de 7.87 % para la cinemática del robot. Esto lleva a que, a través del sistema propuesto, el robot NAO sea capaz de realizar jugadas exitosas con una efectividad promedio del 83.15 %.
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