引用本文: 白云飞, 丛明, 杨小磊, 刘冬. 基于6参数模型的6R串联机器人运动学参数辨识[J]. 机器人, 2015, 37(4): 486-492.
BAI Yunfei, CONG Ming, YANG Xiaolei, LIU Dong. Kinematic Parameter Identification for 6R Serial Robots Based on a 6-Parameter Model[J]. ROBOT, 2015, 37(4): 486-492.
 Citation: BAI Yunfei, CONG Ming, YANG Xiaolei, LIU Dong. Kinematic Parameter Identification for 6R Serial Robots Based on a 6-Parameter Model[J]. ROBOT, 2015, 37(4): 486-492.

Kinematic Parameter Identification for 6R Serial Robots Based on a 6-Parameter Model

• 摘要: 为了避免运动学参数误差辨识中存在参数不连续、计算收敛速度慢的现象，基于一种 6 参数模型，在 DH(Denavit-Hartenberg)法建立的杆件坐标系上建立了 6R 串联机器人的误差模型，并给出了参数转化公式.设计了计算机仿真实验，在存在驱动器、测量仪器随机噪声误差的条件下对比了使用 MDH(改进 DH)参数误差模型和 6 参数模型的仿真辨识效果.6 参数模型和 MDH 模型辨识后定位平均误差分别降低了 96.1% 和 52.9%.结果显示 6 参数模型具有良好的完备性、连续性.6 参数模型的误差参数范围可以从制造公差中得出，辨识速度高于 MDH 模型，通过公差控制参数范围，消除了没有达到极小性要求对误差辨识的影响.应用此方法对一台 SR165 型机器人进行参数辨识，定位平均误差由 2.5mm 降低至 0.35mm.

Abstract: To avoid discontinuous parameters and low-speed convergence in kinematic parameter error identification, an error model for 6R serial robots based on a 6-parameter model is established in the link coordinate systems set up with DH (Denavit-Hartenberg) method. A formula for parameter conversion is derived. In order to compare the results produced by the MDH (modified DH) model and the 6-parameter model, a computer simulation experiment in presence of random noise errors in drives and measuring instruments is designed. The average absolute error is decreased by 96.1% and 52.9% respectively by using the 6-parameter model and the MDH model. The results show that the 6-parameter model has completeness and continuity. The range of model parameters can be derived from the manufacturing tolerances. The 6-parameter model is superior to the MDH model in terms of identification speed. By limiting the parameter range, the influence of lack-of-minimality on error identification is eliminated. The method is applied to parameter identification of an SR165 robot, and the average positioning error is reduced from 2.5 mm to 0.35 mm.

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