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Autonomous torque sensor calibration and gravity compensation for robot manipulators.

机译:机器人机械手的自主扭矩传感器校准和重力补偿。

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摘要

This thesis addresses calibration of joint torque sensors and identification of a gravity compensation (GComp) model. The two problems are related: calibrated torque information is prerequisite for the GComp model identification; the identified GComp model makes on-line automatic torque sensor calibration possible.; In the first part, we propose an autonomous joint torque sensor calibration method, which utilizes combinations of single-joint rotations and an arm's own gravity load. The method determines not only joint torque sensor gains and offsets, but also those of the joint angle sensors. When one joint of a manipulator is rotated, the gravity torque exerted on the joint varies sinusoidally with rotation angle. From the fitted parameters one may extract sensor gains and offsets. A custom designed calibration load is used to provide a reference torque for torque sensor gain calibration. A key feature of the proposed method is that nothing is assumed known about the arm's inertial parameters or of the location of the reference load in the grasp. Experiments are conducted on the Sarcos Dextrous Arm.; The second part of the thesis presents a new and simple procedure to identify link mass parameters used for gravity compensation and on-line automatic torque sensor calibration for a robot manipulator. The approach employs a single-joint rotation and a recursive procedure that proceeds distally to proximally. Composite mass moments are identified for each link, and are further divided into configuration dependent and independent terms. It is shown that the configuration-independent terms may actually combine contributions from several links. Simulation and experimental results on the Sarcos Dextrous Arm verify the approach.
机译:本文着眼于关节扭矩传感器的标定和重力补偿模型的辨识。这两个问题相关:校准的扭矩信息是GComp模型识别的前提;识别出的GComp模型使在线自动扭矩传感器校准成为可能。在第一部分中,我们提出了一种自主的关节扭矩传感器校准方法,该方法利用了单关节旋转和手臂自身的重力载荷的组合。该方法不仅确定关节扭矩传感器的增益和偏移,还确定关节角度传感器的增益和偏移。当机械手的一个关节旋转时,施加在关节上的重力转矩会随旋转角度呈正弦变化。从拟合的参数中,可以提取传感器增益和偏移。使用定制设计的校准负载为扭矩传感器增益校准提供参考扭矩。所提出的方法的一个关键特征是,假设关于手臂的惯性参数或参考负载在抓地力中的位置,一无所知。实验在Sarcos Dextrous Arm上进行。论文的第二部分提出了一种新的,简单的过程,以识别用于机器人操纵器的重力补偿和在线自动扭矩传感器校准所用的连杆质量参数。该方法采用单关节旋转和从远端到近端进行的递归程序。为每个链节确定复合质量矩,并将其进一步分为与配置有关的术语和与独立项无关的术语。结果表明,独立于配置的术语实际上可以组合来自几个链接的贡献。 Sarcos Dextrous Arm的仿真和实验结果验证了该方法。

著录项

  • 作者

    Ma, Donghai.;

  • 作者单位

    McGill University (Canada).;

  • 授予单位 McGill University (Canada).;
  • 学科 Engineering Mechanical.
  • 学位 M.Eng.
  • 年度 1996
  • 页码 89 p.
  • 总页数 89
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 机械、仪表工业;
  • 关键词

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