A Smart Control Device for Human-Machine Gobang (Tic-Tac-Toe) Game

This paper proposes a three pieces game device based on machine vision and intelligent control for the limitations of traditional three pieces game. The device uses an integrated OpenART camera for image acquisition and LAB color space for accurate recognition of the chess board and pieces. First, the camera is calibrated to ensure the accuracy of image acquisition; subsequently, the coordinates of the chessboard grid, the border, and the color and position of the pieces are identified by image preprocessing and target detection algorithms. On this basis, the device adopts a geometric method to solve the robotic arm to realize the accurate picking up and placing of chess pieces. Experiments show that the device can accurately recognize the state of the board, quickly respond to the player's commands, and show good stability and intelligence in the process of the game. The three pieces game device not only provides players with a new game experience, but also demonstrates the prospect of the wide application of machine vision and intelligent control in the game field.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/iaecst64597.2024.11118185
Citations
2
Primary Topic
Digital Games and Media
Type
article
Field-Weighted Citation Impact
2.26
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article

A Smart Control Device for Human-Machine Gobang (Tic-Tac-Toe) Game

Jinyang Gao, Xin Wang, Yeheng Li, Zhaohui Tong
2 citations
Digital Games and Media
2.26
article

A Smart Control Device for Human-Machine Gobang (Tic-Tac-Toe) Game

Jinyang Gao, Xin Wang, Yeheng Li, Zhaohui Tong
article en
2 citations

Abstract

This paper proposes a three pieces game device based on machine vision and intelligent control for the limitations of traditional three pieces game. The device uses an integrated OpenART camera for image acquisition and LAB color space for accurate recognition of the chess board and pieces. First, the camera is calibrated to ensure the accuracy of image acquisition; subsequently, the coordinates of the chessboard grid, the border, and the color and position of the pieces are identified by image preprocessing and target detection algorithms. On this basis, the device adopts a geometric method to solve the robotic arm to realize the accurate picking up and placing of chess pieces. Experiments show that the device can accurately recognize the state of the board, quickly respond to the player's commands, and show good stability and intelligence in the process of the game. The three pieces game device not only provides players with a new game experience, but also demonstrates the prospect of the wide application of machine vision and intelligent control in the game field.

Dalian Jiaotong University (CN)
Openalex Percentile: Top 9%
Digital Games and Media
2.26
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