刘洁, 平雪良, 齐飞, 蒋毅. 基于视觉跟踪的机器人测量方法与实现[J]. 应用光学, 2016, 37(5): 686-692. DOI: 10.5768/JAO201637.0502003
引用本文: 刘洁, 平雪良, 齐飞, 蒋毅. 基于视觉跟踪的机器人测量方法与实现[J]. 应用光学, 2016, 37(5): 686-692. DOI: 10.5768/JAO201637.0502003
Liu Jie, Ping Xueliang, Qi Fi, Jiang Yi. Method and implementation of robot measurement based on visual tracking[J]. Journal of Applied Optics, 2016, 37(5): 686-692. DOI: 10.5768/JAO201637.0502003
Citation: Liu Jie, Ping Xueliang, Qi Fi, Jiang Yi. Method and implementation of robot measurement based on visual tracking[J]. Journal of Applied Optics, 2016, 37(5): 686-692. DOI: 10.5768/JAO201637.0502003

基于视觉跟踪的机器人测量方法与实现

Method and implementation of robot measurement based on visual tracking

  • 摘要: 为了对自主研发的工业机器人进行校准从而提高其运动精度,提出一种采用双目视觉动态跟踪球面编号靶点的机器人标定方法,利用安装在机器人末端靶球上特征分布的编号标志点进行工作空间内任意位姿的测量,由最小二乘迭代准确辨识出机器人的几何结构参数对控制器进行补偿。利用MFC由开放式、模块化思想编制标定软件,设计视觉测量、数据处理、机器人控制等功能模块,最后通过测量实例和对比实验,验证其可靠性和准确性。实验表明,该软件测量得到的位姿数据具有较高的精度,扩大了传统视觉跟踪的视野范围;同时将识别得到的机器人模型实际几何参数进行反馈补偿,成功地将机器人绝对位置精度由3.785 mm提高到1.618 mm,姿态精度由0.235 提高到0.139。

     

    Abstract: In order to calibrate the selfdeveloped industrial robot and improve its movement accuracy, a robot calibration method of dynamic tracking spherical target number by binocular vision was put forward. First we carried out the arbitrary position and orientation measurements in the workspace by markedtargets set on the sphere surface installed on the robotend, which was distinguished and numbered by the particular arrangement and distribution, then accurately identified the geometry parameters of the robot by a leastsquare iterative and compensated them to controller.We established the calibration software including vision measurement, data processing, robot control and other modules by using MFC based on open, modular ideology, finally verified its reliability and accuracy by measuring examples and comparative experiments. Experimental results show that the pose data measured by the software is precise, expanding the field of view of traditional visual tracking; and the identified actual geometry parameters can be compensated, successfully improving the robot positioning accuracy from 3.785 mm to 1.618 mm, as well as the orientation accuracy from 0.235 to 0.139.

     

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