Stone, Paper, Scissors Mini-Game for AI Pet Robot

Aditya Satish Aspat(1*), Elton Lemos(2), Abhishek Ghoshal(3),

(1) Xavier Institute of Engineering, Mumbai University
(2) Xavier Institute of Engineering, Mumbai University
(3) Xavier Institute of Engineering, Mumbai University
(*) Corresponding Author

Abstract


The Artificial Intelligence(AI) Pet Robot is a combination of various fields of computer science. This paper showcases the various functionalities of our AI Pet. Most of the functionalities showcased use the immage processing modules made available through OpenCV. The pet robot has various features such as emotion recognition, follow routine, mini-game etc. This paper discusses the mini-game aspect  of the robot. The game has been developed by using VGG16 convolutional network for identification of the action performed by the user. To improve the accuracy we have made use of background subtraction which gives removes all the unwanted objects from the background and gives a simple cutout of the users hand.

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References


Healthy Pets, Healthy People. U.S. Department of Health & Human Services. https://www.cdc.gov/healthypets/healthbenefits/index.html (Accessed: 02/03/2020).

E. Paul Cherniack, MD and Ariella R. Cherniack, “Assessing the benefits and risks ofowning a pet.” Canadian Medical Association Journal, 2015.

The life and death of Tamagotchi and the virtual pet, https://wellcomecollection.org/articles/WsT4Ex8AAHruGfWb (Accessed: 13/08/2020).

S. Aibo: The Dog and Personal Assistant of the Future, https://www.forbes.com/sites/moorinsights/2019/05/01/sony-aibo-the-dog-and-personal-assistant-of-the-future (Accessed: 05/03/2020).

pibo, https://pibo.circul.us (Accessed: 05/03/2020).

Simonyan, K. Zisserman and Andrew. Very Deep Convolutional Networks for Large-Scale Image Recognition. arXiv 1409.1556, 2014.

Step by step VGG16 implementation in Keras for beginners, https://towardsdatascience.com/step-by-step-vgg16-implementation-in-keras-for-beginners-a833c686ae6c (Accessed: 08/03/2020).

Using Background Subtraction, https://docs.opencv.org/master/d1/dc5/tutorial background subtraction.html (Accessed: 10/03/2020).




DOI: https://doi.org/10.24071/ijasst.v3i1.2754

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