Industrial robot end effector pose repeatability test based on IGCF and CSF-PPSO-ESN algorithm
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TP212 TH86

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    Abstract:

    Industrial robots play an essential role in intelligent manufacturing. The repeatability of the end effector is an important indicator to measure the robot′s ability to complete precision operation. In this article, a theoretical model of the robot end effector′s pose repeatability accuracy measurement is proposed, which is based on directional cosine. A pose deviation detection method is designed, which is based on the improved Gaussian curve fitting (IGCF) algorithm and cubic spline fitting-Pareto particle swarm optimization-echo state network (CSF-PPSO-ESN) algorithm. The measurement of the robot end effector′s pose repeatability accuracy is realized by acquiring the cross-laser pattern′s offset angle and center point position. The experimental results show that the position measurement error after compensation is ±1. 5 μm, and the angle measurement error after compensation is ±2 arc-sec. The proposed pose deviation detection method provides a reference for the online real-time measuring of the robot end effector′s pose repeatability accuracy.

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  • Received:
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  • Online: September 20,2023
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