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Kinematic-Parameter Identification for Serial-Robot Calibration Based on POE Formula

机译:基于POE公式的串行机器人标定运动学参数辨识。

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This paper presents a generic error model, which is based on the product of exponentials (POEs) formula, for serial-robot calibration. The identifiability of parameters in this error model was analyzed. The analysis shows the following: 1) Errors in all joint twists are identifiable. 2) The joint zero-position errors and the initial transformation errors cannot be identified when they are involved in the same error model. With either or neither of them, three practicable error models were obtained. The joint zero-position errors are identifiable when the following condition is satisfied: Coordinates of joint twists are linearly independent. 3) The maximum number of identifiable parameters is 6$n$ + 6 for an $n$-degree-of-freedom (DOF) generic serial robot. Simulation results show the following: 1) The maximum number of identifiable parameters is 6$r$ + 3$t$ + 6, where $r$ is the number of revolute joints, and $t$ is the number of prismatic joints. 2) All the kinematic parameters of the selective compliant assembly robot arm (SCARA) robot and programmable universal machine for assembly (PUMA) 560 robots were identified by using the three error models, respectively. The error model based on the POE formula can be a complete, minimal, and continuous kinematic model for serial-robot calibration.
机译:本文提出了一种通用误差模型,该模型基于指数乘积(POE)公式的乘积,用于串行机器人校准。分析了该误差模型中参数的可识别性。分析显示以下内容:1)可以识别所有关节扭曲中的错误。 2)当联合零位置误差和初始变换误差包含在同一误差模型中时,无法识别它们。无论有没有,都获得了三个可行的误差模型。满足以下条件时,可以识别关节零位置误差:关节扭转的坐标是线性独立的。 3)对于$ n $自由度(DOF)通用串行机器人,最大可识别参数为6 $ n $ + 6。仿真结果表明:1)可识别参数的最大数量为6 $ r $ + 3 $ t $ + 6,其中$ r $是旋转关节的数量,$ t $是棱柱形关节的数量。 2)分别通过使用三个误差模型来识别选择性兼容装配机械臂(SCARA)机器人和可编程通用装配机械(PUMA)560机器人的所有运动学参数。基于POE公式的误差模型可以是用于串行机器人校准的完整,最小和连续的运动学模型。

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