Abstract
Industrial robot has an increasingly wide application in automatic manufacturing of aerospace parts. However, the robot still faces challenges due to the hard processing material and high demand of machining quality. In this paper, a robot posture optimization method is proposed to improve the machining accuracy in aerospace skin milling. The basic idea is that the objective function is defined as absolute average machining accuracy to be minimized. Both joint parameter error and stiffness, the major two factors causing machining error, are considered in the objective function. The function relationship between machining error and joint parameter error is established using robot kinematic. Based on robot dynamics and force adjoint transformation, the machining error with respect to joint stiffness, milling force and robot posture is theoretically analyzed. For n cutting location points, the optimization problem is formulated as (n + 1) variables including rotation and translation redundant freedoms to be determined by genetic algorithm. Finally, the experiment of aerospace skin milling using ABB 6660 robot is provided.
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References
Li, W.L., Xie, H., Zhang, G., Yan, S.J., Yin, Z.P.: Hand–eye calibration in visually-guided robot grinding. IEEE Trans. Cybern. 46(11), 2634–2642 (2016)
Devlieg, R., Sitton, K., Feikert, E., Inman, J.: Once (one-sided cell end effector) robotic drilling system (2002)
Judd, R.P., Knasinski, A.B.: A technique to calibrate industrial robots with experimental verification. IEEE Trans. Robot. Autom. 6(1), 20–30 (1990)
Dolinsky, J.U., Jenkinson, I.D., Colquhoun, G.J.: Application of genetic programming to the calibration of industrial robots. Comput. Ind. 58(3), 255–264 (2007)
Mitsi, S., Bouzakis, K.D., Sagris, D., Mansour, G.: Determination of optimum robot base location considering discrete end-effector positions by means of hybrid genetic algorithm. Robot. Comput.-Integr. Manuf. 24(1), 50–59 (2008)
Schneider, U., Momeni-K, M., Ansaloni, M., Verl, A.: Stiffness modeling of industrial robots for deformation compensation in machining. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 77, pp. 4464–4469. IEEE (2014)
Backer, J.D., Bolmsjö, G.: Deflection model for robotic friction stir welding. Ind. Robot 41(4), 365–372 (2014)
Zargarbashi, S.H.H., Khan, W., Angeles, J.: The jacobian condition number as a dexterity index in 6r machining robots. Robot. Comput. Integr. Manuf. 28(6), 694–699 (2012)
Bu, Y., Liao, W., Tian, W., Zhang, J., Zhang, L.: Stiffness analysis and optimization in robotic drilling application. Precis. Eng. 49, 388–400 (2017)
Palpacelli, M.: Static performance improvement of an industrial robot by means of a cable-driven redundantly actuated system. Pergamon Press Inc, Oxford (2016)
Li, M., Wu, H., Handroos, H.: Stiffness-maximum trajectory planning of a hybrid kinematic-redundant robot machine. In: IECON 2011-37th Annual Conference on IEEE Industrial Electronics Society. vol. 6854, no. 5, pp. 283–288. IEEE (2011)
Colleoni, D., Miceli, G., Pasquarello, A.: Workpiece placement optimization for machining operations with a KUKA KR270-2 robot. In: IEEE International Conference on Robotics and Automation, vol. 147, pp. 2921–2926. IEEE (2013)
Acknowledgement
This work was by the supported by the National Natural Science Foundation of China (No. 51327801, 51535004), the National Basic Research Program of China (No. 2015CB057304), and the Outstanding Youth Foundation of Hubei Province (No. 2017CFA045).
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Xie, H., Li, W., Yin, Z. (2018). Posture Optimization Based on Both Joint Parameter Error and Stiffness for Robotic Milling. In: Chen, Z., Mendes, A., Yan, Y., Chen, S. (eds) Intelligent Robotics and Applications. ICIRA 2018. Lecture Notes in Computer Science(), vol 10984. Springer, Cham. https://doi.org/10.1007/978-3-319-97586-3_25
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DOI: https://doi.org/10.1007/978-3-319-97586-3_25
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