Teaching the NAO Robot to Play a Human-Robot Interactive Game

Abstract

This paper presents the background and methodologies used in programming and teaching the humanoid robot NAO to play the game of "Simon Says" with human players. Choreographe programming was used to provide the overall game logic and incorporate NAO's sensory capabilities. OpenPose pose detection and OpenCV APIs were used to develop the image processing components to convert the raw images captured by NAO for pose classification, and the Keras APIs were used to build the Convolutional Neural Network to classify and recognize the player poses.