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Improving Robotic Accuracy through Iterative Teaching
ISSN: 0148-7191, e-ISSN: 2688-3627
To be published on March 10, 2020 by SAE International in United States
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Industrial robots have been around since the 1960s and their introduction into the manufacturing industry has helped in automating otherwise repetitive and unsafe tasks, while also increasing the performance and productivity for the companies that adopted the technology. As the majority of industrial robotic arms are deployed in repetitive tasks, the pose accuracy is much less of a key driver for the majority of consumers (e.g. the automotive industry) than speed, payload, energy efficiency and unit cost. Consequently, manufacturers of industrial robots often quote repeatability as an indication of performance whilst the pose accuracy remains comparatively poor. Due to their lack in accuracy, robotic arms have seen slower adoption in the aerospace industry where high accuracy is of utmost importance. However if their accuracy could be improved, robots offer significant advantages, being comparatively inexpensive and more flexible than bespoke automation. Extensive research has been conducted in the area of improving robotic accuracy through re-calibration of the kinematic model. This approach is often highly complex, and seeks to optimise performance over the whole working volume or a portion thereof, rather than optimising performance of a particular task. In this paper, a method for iteratively teaching poses on a standard industrial robot is presented, and an investigation into the limits on the achievable pose accuracy and the required recalibration period is conducted. Through experimental work on a KUKA KR 240 R2900 ultra robot equipped with a drilling end-effector and measured in 3DoF using a laser tracker, it is demonstrated that the achievable accuracy approaches the stated repeatability of the robot. Finally, investigation results into the accuracy of the robot over short distances to allow small corrections to be applied from these taught poses to compensate for work-piece alignment or thermal effects are presented.
CitationSawyer, D., Tinkler, L., Roberts, N., and Diver, R., "Improving Robotic Accuracy through Iterative Teaching," SAE Technical Paper 2020-01-0014, 2020.
- Moller, C., Schmidt, H.C., Koch, P. et al. , “Machining of Large Scaled CFRP-Parts with Mobile CNC-Based Robotic System in Aerospace Industry,” Procedia Manufacturing 14:17-29, 2017, https://doi.org/10.1016/j.promfg.2017.11.003.
- Veitschegger, W.K. and Wu, C.H. , “Robot Calibration and Compensation,” IEEE Journal of Robotics and Automation 4(6):643-656, 1988, https://doi.org/10.1109/56.9302.
- Alici, G. and Shirinzadeh, B. , “A Systematic Technique to Estimate Positioning Errors for Robot Accuracy Improvement Using Laser Interferometry Based Sensing,” Mechanism and Machine Theory 40(8):879-906, 2005, https://doi.org/10.1016/j.mechmachtheory.2004.12.012.
- Elatta, A.Y., Gen, L.P., Zhi, F.L. et al. , “An Overview of Robot Calibration,” Information Technology Journal 3(1):74-78, 2004, https://doi.org/10.3923/itj.2004.74.78.
- Slamani, M., Nubiola, A., and Bonev, I. , “Assessment of the Positioning Performance of an Industrial Robot,” Industrial Robot: An International Journal 39(1):57-68, 2012, https://doi.org/10.1108/01439911211192501.
- Schneider, U., Drust, M., Ansaloni, M. et al. , “Improving Robotic Machining Accuracy through Experimental Error Investigation and Modular Compensation,” The International Journal of Advanced Manufacturing Technology 85(1-4):3-15, 2016, https://doi.org/10.1007/s00170-014-6021-2.
- Zhang, J., Wang, X., Wen, K. et al. , “A Simple and Rapid Calibration Methodology for Industrial Robot Based on Geometric Constraint and Two-Step Error,” Industrial Robot: An International Journal 45(6):721-751, 2018, https://doi.org/10.1108/IR-05-2018-0102.
- Xiaoyan, C., Qiuju, Z., and Yilin, S. , “Non-Kinematic Calibration of Industrial Robots Using a Rigid-Flexible Coupling Error Model and a Full Pose Measurement Method,” Robotics and Computer-Integrated Manufacturing 57:46-58, 2019, https://doi.org/10.1016/j.rcim.2018.07.002.
- Joubair, A. and Bonev, I.A. , “Non-Kinematic Calibration of a Six-Axis Serial Robot Using Planar Constraints,” Precision Engineering 40:325-333, 2015, https://doi.org/10.1016/j.precisioneng.2014.12.002.
- KUKA Robotics , “Manual KUKA Series 2000,” 2019.
- DeVlieg, R. and Szallay, T. , “Improved Accuracy of Unguided Articulated Robots,” SAE Int. J. Aerosp. 2(1):40-45, 2010, https://doi.org/10.4271/2009-01-3108.