当前位置: X-MOL 学术Robot. Comput.-Integr. Manuf. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A vision-based fast base frame calibration method for coordinated mobile manipulators
Robotics and Computer-Integrated Manufacturing ( IF 9.1 ) Pub Date : 2020-10-16 , DOI: 10.1016/j.rcim.2020.102078
Qi Fan , Zeyu Gong , Shiyi Zhang , Bo Tao , Zhouping Yin , Han Ding

The mobile manipulators (MMs) have been increasingly adopted for machining large and complex components. In order to ensure the machining efficiency and quality, the MMs usually need to cooperate with each other. However, due to the low motion accuracy of the mobile platform, the relative pose accuracy between the coordinated MMs are difficult to guarantee, so an effective calibration method is needed to on-line obtain the relative pose of the MMs. For this purpose, a vision-based fast base frame calibration method is proposed in this paper, which can quickly and accurately obtain the relative pose between the coordinated MMs. The method only needs to add a camera and a marker, and then a frame network of the calibration system can be generated by installing the marker at three different positions. Based on the Perspective-n-Points principle and the robot forward kinematics, the transformation matrix of the marker frame with respect to the camera frame and the robot base frame can be determined by simply obtaining the images of the marker at different positions and corresponding robot joint angles. Then, the relative pose between the base frames of coordinated MMs can be determined by the calibration equation established based on a frame closed chains. In addition, the calibration method is capable of real-time calculation by dividing the calibration process into off-line and on-line stages. Simulation and experimental results have verified the effectiveness of the proposed method.



中文翻译:

基于视觉的协同移动机械手快速基架标定方法

移动机械手(MM)已越来越多地用于加工大型和复杂的零件。为了确保加工效率和质量,MM通常需要相互配合。然而,由于移动平台的运动精度低,难以保证协调MM之间的相对姿态精度,因此需要一种有效的校准方法来在线获得MM的相对姿态。为此,本文提出了一种基于视觉的快速基帧标定方法,该方法可以快速,准确地获得协调坐标系之间的相对姿态。该方法仅需添加摄像机和标记器,然后通过将标记器安装在三个不同的位置即可生成校准系统的框架网络。基于“透视n点”原理和机器人正向运动学,只需简单地获取标记在不同位置和相应机器人的图像,就可以确定标记框相对于相机框架和机器人基础框架的转换矩阵。关节角度。然后,可以通过基于框架闭合链建立的校准方程式来确定坐标MM的基本框架之间的相对姿态。另外,通过将校准过程分为离线和在线阶段,校准方法能够进行实时计算。仿真和实验结果证明了该方法的有效性。通过简单地获得标记在不同位置和相应的机器人关节角度处的图像,可以确定标记架相对于摄像机框架和机器人基础框架的变换矩阵。然后,可以通过基于框架闭合链建立的校准方程式来确定坐标MM的基本框架之间的相对姿态。另外,通过将校准过程分为离线和在线阶段,校准方法能够进行实时计算。仿真和实验结果证明了该方法的有效性。通过简单地获得标记在不同位置和相应的机器人关节角度处的图像,可以确定标记架相对于摄像机框架和机器人基础框架的变换矩阵。然后,可以通过基于框架闭合链建立的校准方程式来确定坐标MM的基本框架之间的相对姿态。另外,通过将校准过程分为离线和在线阶段,校准方法能够进行实时计算。仿真和实验结果证明了该方法的有效性。可以通过基于框架闭合链建立的校准方程式来确定坐标MM的基本框架之间的相对姿态。另外,通过将校准过程分为离线和在线阶段,校准方法能够进行实时计算。仿真和实验结果证明了该方法的有效性。可以通过基于框架闭合链建立的校准方程式来确定坐标MM的基本框架之间的相对姿态。另外,通过将校准过程分为离线和在线阶段,校准方法能够进行实时计算。仿真和实验结果证明了该方法的有效性。

更新日期:2020-10-17
down
wechat
bug