Implementing a rock-paper-scissors game

[mxochicale]

@Diego-Coyotzi-M @eliasmendez2514 and I discussed the potential application of Machine Learning to program the game of the rock, paper sissors.

The following are potential references:

LearningML by Juan David Rodríguez

Site: https://web.learningml.org/en/learningml-in-the-biweekly-seminars-of-the-raspberry-pi-foundation/ Slides: https://www.raspberrypi.org/app/uploads/2020/05/Learning-AI-at-school-with-Scratch-and-LearningML.pdf Video: https://www.youtube.com/watch?v=vRY4v1diuhA&feature=emb_title Paper: https://ieeexplore.ieee.org/document/8970124

[mxochicale]

Just made a quick search and there are various tutorials in youtube. Perhaps, we need to check the compatibility of hardware and robots. For istnace in terms of hardware, we might like to think about:

• https://www.okdo.com/p/official-raspberry-pi-camera-v2-1

[mxochicale]

Just found a similar projects but sort of advance project using raspberry pi

Janken (rock-paper-scissors) Robot with 100% winning rate: 3rd version

https://www.youtube.com/watch?v=Qb5UIPeFClM&t=3s

The third version of the Janken (rock-paper-scissors) robot with 100% winning rate has been developed. In this version, we incorporated the high-speed tracking technologies "1ms Auto Pan-Tilt" and "Lumipen 2" in order to extend a field of view of the high speed vision system. The inclusion of these technologies additionally enables the system to dynamically track the human hand and recognize its shape in high speed, regardless of where it moves, as well as improves the synchronization between the motion of the robot hand and that of the human hand. Using high-speed vision together with the high-speed actuation of the robot hand enables the robot to achieve a 100 % winning rate. Janken Robot Web: http://ishikawa-vision.org/fusion/Janken/index-e.html Lumipen 2 YouTube Video https://www.youtube.com/watch?v=p7IL0Gvux7U

A Rock-Paper-Scissors game using computer vision and machine learning on Raspberry Pi.

Another project is "A Rock-Paper-Scissors game using computer vision and machine learning on Raspberry Pi." By Julien de la Bruère-Terreault (drgfreeman@tuta.io) which repository is here: https://github.com/DrGFreeman/rps-cv . See more: https://www.thingiverse.com/thing:2598378

[mxochicale]

Diego shared the following points:

• https://uelectronics.com/producto/esp32-cam-ov2640-wifi-bluetooth/
• https://media.digikey.com/pdf/Data%20Sheets/DFRobot%20PDFs/DFR0602_Web.pdf
• https://articulo.mercadolibre.com.mx/MLM-580908442-camara-arduino-ov7670-_JM?matt_tool=48904454&matt_word=&matt_source=google&matt_campaign_id=11714912137&matt_ad_group_id=113017550359&matt_match_type=&matt_network=g&matt_device=c&matt_creative=482511924687&matt_keyword=&matt_ad_position=&matt_ad_type=pla&matt_merchant_id=143841145&matt_product_id=MLM580908442&matt_product_partition_id=353037831509&matt_target_id=pla-353037831509&gclid=Cj0KCQjw6ZOIBhDdARIsAMf8YyEH73w25R0ePrpwG2y-XYsnWAvlFQ2Uj6Mq

[mxochicale]

Tiny Machine Learning e Inteligencia Artificial con Arduino | Edge Impulse + Wio Terminal

Good example but perhaps it is not necessary to use Wio but only a light sensor (camera) with Edge impulse. video: https://www.youtube.com/watch?v=qacGLRnimqY