首页|基于视觉的并联机床位姿测量研究

基于视觉的并联机床位姿测量研究

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为准确测量并联机床的位姿,提高并联机床的运动精度,提出一种基于视觉的位姿测量方法用于并联机构的末端位姿检测。采用Femto深度相机作为测量设备搭建测量平台,并用棋盘格标定板和MATLAB对相机进行标定;将标靶置于动平台进行位姿采集,利用点云库对采集后的数据进行过滤和提取;最后,将计算出的实际位姿与输入位姿进行实验比较。结果表明:X、Y、Z轴的最大误差分别为 0。071、0。047、0。394 mm,绕 X、Y、Z 轴旋转的最大误差分别为 0。09°、0。09°、0。14°,满足精度要求,证明了此方法的有效性。此方法操作高效便捷、成本低廉,在保证高检测精度的同时,可为位姿测量和后续标定实验提供新思路。
Research on Pose Measurement of Parallel Machine Tools Based on Vision
To accurately measure the pose of a parallel machine tool and improve its motion precision,a vision-based pose meas-urement method for end pose detection in parallel mechanisms was proposed.A measurement platform was built using the Femto depth camera as the measurement device,and the camera was calibrated using a chessboard pattern and MATLAB.A target was placed on the moving platform to collect pose data,and the collected data were filtered and extracted using a point cloud database.Finally,the calculat-ed actual poses were experimentally compared with the input poses.The results show that the maximum errors on the X,Y and Z axis are 0.071 mm,0.047 mm,and 0.394 mm respectively,the maximum errors of rotating around the X,Y and Z axis are 0.09°,0.09° and 0.14° respectively,which meets the accuracy requirements and confirms the effectiveness of the proposed method.The proposed method offers efficient and convenient operation with low cost,and while ensuring high detection accuracy.It can provide new ideas for pose measurement and subsequent calibration experiments.

parallel machine toolpoint cloud processingFemto depth camerapose measurement

张天虎、钟建琳、彭宝营、王鹏家

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北京信息科技大学机电工程学院,北京 100192

并联机床 点云处理 Femto深度相机 位姿测量

2024

机床与液压
中国机械工程学会 广州机械科学研究院有限公司

机床与液压

CSTPCD北大核心
影响因子:0.32
ISSN:1001-3881
年,卷(期):2024.52(16)