广东工业大学学报 ›› 2023, Vol. 40 ›› Issue (01): 77-82,91.doi: 10.12052/gdutxb.210098

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围棋机器人落子指引装置的设计与实现

邹恒1, 高军礼1, 张树文1, 宋海涛2   

  1. 1. 广东工业大学 自动化学院，广东 广州 510006;
    2. 华南理工大学 工商管理学院，广东 广州 510640
  • 收稿日期:2021-07-06 出版日期:2023-01-25 发布日期:2023-01-12
  • 通信作者: 高军礼(1973-),男,副教授,博士,主要研究方向为机器人感知与人机交互,E-mail:13826067859@163.com
  • 作者简介:邹恒(1994-),男,硕士研究生,主要研究方向为图像处理与运动控制
  • 基金资助:
    广东省科技计划项目(2015B010114004)

Design and Implementation of a Dropping Guidance Device for Go Robot

Zou Heng1, Gao Jun-li1, Zhang Shu-wen1, Song Hai-tao2   

  1. 1. School of Automation, Guangdong University of Technology, Guangzhou 510006, China;
    2. School of Business Administration, South China University of Technology, Guangzhou 510640, China
  • Received:2021-07-06 Online:2023-01-25 Published:2023-01-12

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摘要： 为提升围棋对弈与教学过程中的交互性，设计了一种用于围棋机器人的落子指引装置，包括视觉处理模块与运动控制模块。针对视觉处理模块，提出一种基于多尺度检测的标准棋盘图像提取方法，提高了棋盘图像提取的稳定性。对棋盘中的反光区域采用单独的棋子检测器进行检测，提高了不均匀光照区域棋子的检测效果。针对运动控制模块，利用高精度数字舵机和激光指引器构建运动执行机构，并采用伸缩关节模拟激光光路实现运动学建模。提出一种基于透视变换的误差补偿方法，实现关节变量的映射，并通过仿真计算完成运动末端位置补偿。最后，通过实验对视觉模块的准确性与运动控制模块误差补偿方法的有效性进行了验证。

关键词: 图像处理, 运动学建模, 透视变换, 误差补偿, 围棋机器人

Abstract: In order to improve the interaction between go playing and teaching, a drop guidance device for go robot is designed, including visual processing and motion control modules. For the visual processing module, a standard chessboard image extraction method based on multi-scale detection is proposed to improve the stability of chessboard image extraction. A separate chessboard detector is used to detect the pieces in the reflective area of the chessboard, and the detection effect of chess pieces in uneven illumination area is improved. For the motion control module, the high-precision digital actuators and laser guider are used to construct the motion actuator. The kinematics modeling is completed by using the telescopic joint to simulate the laser light path. An error compensation method based on perspective transformation is proposed to realize the mapping of joint variables. The motion end position compensation is implemented through simulation calculation. Finally, the accuracy of vision module and the effectiveness of error compensation method of motion control module are verified experimentally.

Key words: image processing, kinematics modeling, perspective transformation, error compensation, go robot

中图分类号: 

  • TP391.4
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