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
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
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
网络首发:2023-01-25,
纸质出版:2023
移动端阅览
邹恒, 高军礼, 张树文, 宋海涛. 围棋机器人落子指引装置的设计与实现[J]. 广东工业大学学报, 2023, 40(1): 77-82, 91.
Zou Heng, Gao Jun-li, Zhang Shu-wen, et al. Design and Implementation of a Dropping Guidance Device for Go Robot[J]. 2023, 40(1): 77-82, 91.
邹恒, 高军礼, 张树文, 宋海涛. 围棋机器人落子指引装置的设计与实现[J]. 广东工业大学学报, 2023, 40(1): 77-82, 91. DOI: 10.12052/gdutxb.210098.
Zou Heng, Gao Jun-li, Zhang Shu-wen, et al. Design and Implementation of a Dropping Guidance Device for Go Robot[J]. 2023, 40(1): 77-82, 91. DOI: 10.12052/gdutxb.210098.
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。
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.
ZHAGN S, YAN H Z, HAN F L, et al . Design of go robot controller based on ARM and freeRTOS [J ] . Manufacturing Automation, 2018, 40(1): 28-32.
MATUSZEK C, MAYTON B, AIMI R, et al. Gambit: an autonomous chess-playing robotic system[C]//2011 IEEE International Conference on Robotics and Automation. Shanghai: IEEE, 2011: 4291-4297.
KOOSOWSKI P, WOLNIAKOWSKI A, MIATLIUK K. Collaborative robot system for playing chess[C]//2020 International Conference Mechatronic Systems and Materials (MSM) . Bialytok, Poland: IEEE, 2020.
WANG H B, SHI M. Recognizing chessboard and positioning checkboard in Chinese chess game System[C]//2014 Fourth International Conference on Communication Systems and Network Technologies (CSNT 2014) . Bhopal, India: IEEE, 2014: 1182-1186.
SONG J. LI S S. A robust algorithm for Go image recognition in Go game[C]//2018 IEEE 4th International Conference on Computer and Communications (ICCC) . Chengdu: IEEE, 2018: 1397-1401.
SONG J, YANG M Z. A calibration method for the vision system of go-robot[C]//2019 6th International Conference on Systems and Informatics (ICSAI) . Shanghai: IEEE, 2019: 1157-1162.
WANG Y J, ZHANG Y B, WU Y Y, et al . General chess piece positioning method under uneven illumination [J ] . Journal of Computer Applications, 2020, 40(12): 3490-3498.
SHI X J, ZHANG F M, QU X H, et al . Position and attitude measurement and online errors compensation for KUKA industrial robots [J ] . Journal of Mechanical Engineering, 2017, 53(8): 1-7.
WANG L F, LI X, ZHANG L Y, et al . Analysis of the positioning error of industrial robots and accuracy compensation based on ELM algorithm [J ] . Robot, 2018, 40(6): 843-851.
杨文韬, 詹军, 佘勇, 等. 工业机器人绝对定位精度优化方法综述[J]. 表面工程与再制造, 2019, 19(2): 28-32.
ZHOU W, LIAO W H, TIAN W. Theory and experiment of industrial robot accuracy compensation method based on spatial interpolation [J]. Journal of Mechanical Engineering, 2013, 49(3): 42-48.
ZHOU W, LIAO W H, TIAN W, et al . Method of industrial robot accuracy compensation based on particle swarm optimization neural network [J ] . China Mechanical Engineering, 2013, 24(2): 174-179.
ANGELIDIS A, VOSNIAKOS G C. Prediction and compensation of relative position error along industrial robot end-effector paths [J]. International Journal of Precision Engineering and Manufacturing, 2014, 15: 63-73.
SHI J B, TOMASI C. Good features to track[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Seattle, WA, USA: IEEE, 1994: 593-600.
LI P J, LI J Z, SONG Y, et al . Error analysis of unmanned aerial vehicle remote sensing images stitching based on simulation [J ] . Journal of Computer Applications, 2015, 35(4): 1116-1119.
0
浏览量
0
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621