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Computer vision based robot calibration and control.

机译:基于计算机视觉的机器人校准和控制。

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摘要

To use a robot for tasks that require high accuracy, parametric calibration, a one-time affair, or an external sensing system is necessary. An external measuring system is more advantageous because it can be used to maintain high accuracy performance on-line. Such a system should be capable of measuring the end effector pose (position and orientation) of the robot in real-time. With such a measuring system, robot repeatability and accuracy can be measured and then used in task design. The objective of this dissertation is to demonstrate the use of a single camera 3D computer vision (SCV) system as a pose (position and orientation) sensor in order to perform robot calibration. The proposed SCV system (furnished by IBM) used in this dissertation is capable of accurately measuring movements in the 0.001 inch (0.005 cm), and 0.05 degree ranges. Other systems will perform differently since measurements are dependent upon the field of view and the camera resolution. A vision feedback scheme, termed Vision-guided Robot Control (VRC), is described which can improve the accuracy of a robot in an on-line iterative manner. This system demonstrates the advantage that can be achieved by a Cartesian space robot control scheme when end effector position/orientation is sensed instead of calculated from the kinematic equations. The degree of accuracy is determined by setting a tolerance level that is within the camera system's accuracy for each of the six robot Cartesian space coordinates. In general, a small tolerance level requires many iterations to position the end effector, and a large tolerance level requires fewer iterations. The viability of using a vision system for robot calibration is demonstrated by experimentally showing that the accuracy of an industrial robot can be drastically improved. In addition, the vision system can be used to measure the repeatability and accuracy of a robot in a simple, efficient, and quick manner. Experimental work utilizing an IBM Electric Drive Robot (EDR) and an SCV system produced a 97 and a 145 fold improvement in the position and orientation accuracy of the robot, respectively. For biomedical applications, this system can serve as a safety precaution during surgery, i.e. the surgical removal of bone by a robot. The use of a robot system insures a tight fit between the prosthesis and the bone interface for a total hip replacement procedure (a medical robotic system under development at U.C. Davis). However, the SCV system can also be used for other tasks that require high accuracy such as electronic assembly and materials handling.
机译:若要将机器人用于需要高精度的任务,则需要进行参数校准,一次性事务或外部传感系统。外部测量系统更具优势,因为它可用于保持在线的高精度性能。这样的系统应该能够实时测量机器人的末端执行器姿势(位置和方向)。使用这种测量系统,可以测量机器人的重复性和准确性,然后将其用于任务设计中。本文的目的是演示使用单摄像头3D计算机视觉(SCV)系统作为姿势(位置和方向)传感器来执行机器人校准。本文中使用的拟议SCV系统(由IBM提供)能够精确地测量0.001英寸(0.005厘米)和0.05度范围内的运动。由于测量取决于视场和相机分辨率,因此其他系统的性能会有所不同。描述了一种称为视觉引导机器人控制(VRC)的视觉反馈方案,该方案可以以在线迭代的方式提高机器人的精度。该系统演示了当感测末端执行器的位置/方向而不是根据运动方程计算时,可以通过笛卡尔空间机器人控制方案实现的优势。通过为六个机器人笛卡尔空间坐标中的每个坐标设置在相机系统精度范围内的公差级别来确定精度程度​​。通常,较小的公差级别需要多次迭代才能定位末端执行器,而较大的公差级别则需要更少的迭代。通过实验证明,可以大幅度提高工业机器人的精度,证明了将视觉系统用于机器人校准的可行性。此外,视觉系统可用于以简单,高效和快速的方式测量机器人的可重复性和准确性。利用IBM Electric Drive Robot(EDR)和SCV系统进行的实验工作分别使机器人的位置和方向精度提高了97倍和145倍。对于生物医学应用,该系统可以用作外科手术期间的安全预防措施,即由机器人进行外科手术去除骨头。机器人系统的使用可确保假体与骨骼界面之间紧密配合,以进行整个髋关节置换手术(美国戴维斯分校正在开发的医疗机器人系统)。但是,SCV系统也可以用于其他要求高精度的任务,例如电子装配和材料处理。

著录项

  • 作者

    Preising, Boris Martin.;

  • 作者单位

    University of California, Davis.;

  • 授予单位 University of California, Davis.;
  • 学科 Engineering Biomedical.
  • 学位 Ph.D.
  • 年度 1990
  • 页码 270 p.
  • 总页数 270
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物医学工程;
  • 关键词

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