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首页> 外文期刊>International Journal of Machine Tools & Manufacture: Design, research and application >Nongeometric error identification and compensation for robotic system by inverse calibration
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Nongeometric error identification and compensation for robotic system by inverse calibration

机译:逆向标定用于机器人系统的非几何误差识别与补偿

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摘要

In order to achieve the stringent accuracy requirement of some robotic applications such as robotic measurement systems, it is critical to compensate for nongeometric errors such as compliance errors and thermal errors in addition to geometric errors. This paper investigates the effect of geometric errors, link compliance and temperature variation on robot positioning accuracy. A comprehensive error model is derived for combining geometric errors, position-dependent compliance errors and time-variant thermal errors. A general methodology is developed to identify these errors simultaneously. A laser tracker is applied to calibrate these errors by an inverse calibration method. Robot geometric errors and compliance errors are calibrated at room temperature while robot parameter thermal errors are calibrated at different temperatures when the robot warms up and cools down. Empirical thermal error models are established using orthogonal regression methods to correlate robot parameter thermal errors with the corresponding temperature field. These models can be built into the controller and used to compensate for quasi-static thermal errors due to internal and external heat sources. Experimental results show that the robot accuracy is improved by an order of magnitude after calibration.
机译:为了达到某些机器人应用(例如机器人测量系统)的严格精度要求,除几何误差外,补偿非几何误差(例如顺应性误差和热误差)至关重要。本文研究了几何误差,链接柔度和温度变化对机器人定位精度的影响。导出了综合的误差模型,用于组合几何误差,与位置有关的依从性误差和时变热误差。开发了一种通用方法来同时识别这些错误。应用激光跟踪仪通过反向校准方法校准这些误差。机器人加热和冷却时,在室温下校准机器人几何误差和柔度误差,而在不同温度下校准机器人参数的热误差。使用正交回归方法建立经验热误差模型,以将机器人参数热误差与相应的温度场相关联。这些模型可以内置在控制器中,并用于补偿由于内部和外部热源引起的准静态热误差。实验结果表明,校准后机器人的精度提高了一个数量级。

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