Development of a Non-Parametric Robot Calibration Method to Improve Drilling Accuracy

AeroTech® Digital Summit
Authors Abstract
The drilling of large quantities of repetitive holes during the manufacture of large aerospace components is often considered a key limiting factor with regards to production efficiency. Whilst the desire within aerospace is to use relatively cheap six axis robot arms with drilling end effector units, their poor accuracy remains an obstacle. Robot calibration presents a way of improving robot accuracy such that aerospace drilling tolerances can be met, without permanently committing metrology equipment to an automation cell during production. Extensive research has been conducted into robot calibration by correcting the kinematic model, known as parametric calibration. This method is highly complex, and calibrates the robot across the entire working volume. This is often not required in industrial drilling applications, as drilling routines are often contained within a smaller volume of the robot reach. In this paper, a non-parametric method of robot calibration is proposed. This method involves calibrating within regions of the working volume where the robot pose is similar, and thus the effects of geometric errors in the kinematic model are roughly constant. By establishing the average positional error for each region, the accuracy can be locally improved by compensation through definition of the tool centre point. The proposed method can be completed without the use of kinematic models or complex mathematics, making it more suitable to industrial users. From experimental trials, a significant improvement in the positional accuracy of holes drilled using a standard six axis robot is reported, from 2 mm to 0.1 mm, well within the requirements of the majority of aerospace applications.
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Scraggs, C., Smith, T., Sawyer, D., and Davis, M., "Development of a Non-Parametric Robot Calibration Method to Improve Drilling Accuracy," SAE Int. J. Adv. & Curr. Prac. in Mobility 3(3):1152-1159, 2021,
Additional Details
Mar 2, 2021
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Journal Article