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

被引:1
|
作者
Li, Cen [1 ]
Imeokparia, Ebosehon [1 ]
Ketzner, Michael [1 ]
Tsahai, Tsega [1 ]
机构
[1] Middle Tennessee State Univ, Dept Comp Sci, Murfreesboro, TN 37130 USA
关键词
robotics; computer vision; pose detection; convolutional neural network; image classification;
D O I
10.1109/CSCI49370.2019.00134
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:712 / 715
页数:4
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