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Path Planning Methodology for Multi-Layer Welding of Intersecting Pipes Considering Collision Avoidance

Published online by Cambridge University Press:  10 September 2020

M. Shahabi ,
H. Ghariblu Open the ORCID record for H. Ghariblu [Opens in a new window] ,
M. Beschi  and
N. Pedrocchi
M. Shahabi
Affiliation:
Mechanical Engineering Department, University of Zanjan, Zanjan, Iran
H. Ghariblu*
Affiliation:
Mechanical Engineering Department, University of Zanjan, Zanjan, Iran
M. Beschi
Affiliation:
Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing - National Research Council, Milan, Italy
N. Pedrocchi
Affiliation:
Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing - National Research Council, Milan, Italy
*
*Corresponding author. E-mail: [email protected]
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Summary

The V-groove joint of thick wall intersecting pipes must be filled by multi-layer weld. The welding path of intersecting pipes is complicated, and hence multi-layer welds increase the complexity of the problem. This paper proposes a methodology for path planning of multi-layer weld of thick wall intersecting pipes. The methodology is based on measuring the electrode pose located in both side and front views of intersecting pipes. In order to compensate for the path deviation around the pipe circumference, the measured values are used to interpolate the path of each pass between two views. The methodology has been applied in a case study. Simulation results approve that multi-layer weld appropriately fills the V-groove joint space around the pipe circumference. In addition, collision avoidance between welding torch and pipes is considered by introducing a safety ring. While the robot wrist moves inside the safety ring, no collision occurs. Simulation results show the robustness of the proposed path planning method, introduced for collision avoidance.

Keywords

Path planningMulti-layer welding intersecting pipesObstacle avoidance
Type
Article
Information
Robotica , Volume 39 , Issue 6 , June 2021 , pp. 945 - 958
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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References

Moon, H.-S. and Na, S.-J., “Neuro-Fuzzy System for Predicting Optimal Weld Parameters of Horizontal Fillet Welds,” Proceedings of Asian Pacific Welding Congress (1996).Google Scholar
Kim, Y. B., Kim, J. G., Jang, W. T., Park, J. R., Moon, H. S. and Kim, J. O., “Development of automatic welding system for multi-layer and multi-pass welding,” IFAC Proc. 41(2), 4290–4291 (2008).CrossRefGoogle Scholar
Wu, Y., Go, J. Z. M., Ahmed, S. M., Lu, W., Chew, C. and Pang, C. K., “Automated Bead Layout Methodology for Robotic Multi-Pass Welding,” In: 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA) (IEEE, Luxembourg, 2015) pp. 1–4.Google Scholar
Yang, C., Ye, Z., Chen, Y., Zhong, J. and Chen, S., “Multi-pass path planning for thick plate by DSAW based on vision sensor,” Sens. Rev. 34(4), 416–423 (2014).CrossRefGoogle Scholar
He, Y., Xu, Y., Chen, Y., Chen, H. and Chen, S., “Weld seam profile detection and feature point extraction for multi-pass route planning based on visual attention model,” Robot. Comput. Integr. Manuf. 37, 251–261 (2016).CrossRefGoogle Scholar
Gu, W., Xiong, Z. and Wan, W., “Autonomous seam acquisition and tracking system for multi-pass welding based on vision sensor,” Int. J. Adv. Manuf. Tech. 69(1–4), 451–460 (2013).CrossRefGoogle Scholar
Liu, Y., Liu, J. and Tian, X., “An approach to the path planning of intersecting pipes weld seam with the welding robot based on non-ideal models,” Robot. Comput. Integr. Manuf. 55, 96–108 (2019).CrossRefGoogle Scholar
Xingkui, S., Xinhua, Y. and Yuedong, W., “Modeling and Simulating for Multi-Pass Welding Process of Large Welded Structures,” In: 2010 International Conference on Digital Manufacturing & Automation (IEEE, 2010).CrossRefGoogle Scholar
Zhang, H., Lu, H., Cai, C. and Chen, S., “Robot Path Planning in Multi-Pass Weaving Welding for Thick Plates,” In: Robotic Welding, Intelligence and Automation (Springer, 2011) pp. 351–359.CrossRefGoogle Scholar
Ahmed, S. M., Yuan, J., Wu, Y., Chew, C. M. and Pang, C. K., “Collision-Free Path Planning for Multi-Pass Robotic Welding,” In: 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA) (IEEE, 2015).CrossRefGoogle Scholar
Evensen, B. E., Robotic Multiple-Pass Welding of V-Groove Butt Joints (NTNU, 2016). H. Ghariblu and M. Shahabi, “Path planning of complex pipe joints welding with redundant robotic systems,” Robotica 37(6), 1020–1032 (2019)Google Scholar
Shahabi, M. and Ghariblu, H., “Optimal joint motion for complicated welding geometry by a redundant robotic system,” Eng. Optim. 52(5), 875–895 (2020)Google Scholar
Luo, X., Li, S., Liu, S. and Liu, G. ., “An optimal trajectory planning method for path tracking of industrial robots,” Robotica, 37(3), 502–520 (2019)CrossRefGoogle Scholar
Fang, H., Ong, S. and Nee, A., “Robot path planning optimization for welding complex joints,” Int. J. Adv. Manuf. Tech. 90(9–12), 3829–3839 (2017).CrossRefGoogle Scholar
Lü, Y., Tian, X. and Liang, J., Track Control in Automated Welding of Saddle Curve (2010).Google Scholar
Chen, C., Chen, S. Hu, D. He and J. Shen, “An approach to the path planning of tube–sphere intersection welds with the robot dedicated to J-groove joints,” Robot. Comput. Integr. Manuf. 29(4), 41–48 (2013).CrossRefGoogle Scholar
Zhenyang, L. Y. Z. J. L. and Shujun, C., “Pose planning for the end-effector of robot in the welding of intersecting pipes,” Chin. J. Mech. Eng.-En. 24(2), 1.Google Scholar
Ren, F., Chen, S., Yin, S. and Guan, X., “Modeling on weld position and welding torch pose in welding of intersected pipes,” Trans. China Weld. Ins. 29(11), 33–36 (2008).Google Scholar
Shi, L. and Tian, X., “Automation of main pipe-rotating welding scheme for intersecting pipes,” Int. J. Adv. Manuf. Technol. 77(5–8), 955–964 (2015).CrossRefGoogle Scholar
Shi, L., Tian, X. and Zhang, C., “Automatic programming for industrial robot to weld intersecting pipes,” Int. J. Adv. Manuf. Technol. 81(9–12), 2099–2107 (2015).CrossRefGoogle Scholar
Li, J., Li, L., Dong, Z. and Song, D., “An automatic posture planning software of arc robot based on solidworks API,” Mod. Appl. Sci. 3(7), 121 (2009).CrossRefGoogle Scholar
Liu, Y., Shi, L. and Tian, X., “Weld seam fitting and welding torch trajectory planning based on NURBS in intersecting curve welding,” Int. J. Adv. Manuf. Technol. 95(5–8), 2457–2471 (2018).CrossRefGoogle Scholar
Saramago, S. F. and Junior, V. S., “Optimal trajectory planning of robot manipulators in the presence of moving obstacles,” Mech. Mach. Theory 35(8), 1079–1094 (2000).Google Scholar
Agirrebeitia, J., Avilés, R., de Bustos, I. F. and Ajuria, G., “A new APF strategy for path planning in environments with obstacles,” Mech. Mach. Theory 40(6), 645–658 (2005).Google Scholar
Valero, F., Mata, V. and Besa, A., “Trajectory planning in workspaces with obstacles taking into account the dynamic robot behaviour,” Mech. Mach. Theory 41(5), 525–536 (2006).CrossRefGoogle Scholar
Saravanan, R., Ramabalan, S. and Balamurugan, C., “Evolutionary multi-criteria trajectory modeling of industrial robots in the presence of obstacles,” Eng. Appl. Artif. Intell. 22(2), 329–342 (2009).CrossRefGoogle Scholar
Menasri, R., Nakib, A., Daachi, B., Oulhadj, H. and Siarry, P., “A trajectory planning of redundant manipulators based on bilevel optimization,” Appl. Math. Comput. 250, 934–947 (2015).Google Scholar
Xiao, L. and Zhang, Y., “Dynamic design, numerical solution and effective verification of acceleration-level obstacle-avoidance scheme for robot manipulators,” Int. J. Syst. Sci. 47(4), 932–945 (2016).CrossRefGoogle Scholar
Chen, C., “Path planning in distorted configuration space,” Robotica 35(7), 1585–1597 (2017).CrossRefGoogle Scholar
Abu-Dakka, F. J., Rubio, F., Valero, F. and Mata, V., “Evolutionary indirect approach to solving trajectory planning problem for industrial robots operating in workspaces with obstacles,” Eur. J. Mech.-A/Solids 42, 210–218 (2013).CrossRefGoogle Scholar
Rubio, F. J., et al., “Simultaneous algorithm to solve the trajectory planning problem,” Mech. Mach. Theory 44(10), 1910–1922 (2009).CrossRefGoogle Scholar
Rubio, F., Valero, F., Sunyer, J. L. and Garrido, A., “The simultaneous algorithm and the best interpolation function for trajectory planning,” Ind. Robot Int. J. 37(5), 441–451 (2010).CrossRefGoogle Scholar
Shahabi, M., Ghariblu, H. and Beschi, M., “Obstacle avoidance of redundant robotic manipulators using safety ring concept,” Int. J. Comput. Integr. Manuf. 32(7), 695–704 (2019).CrossRefGoogle Scholar
Fahimi, F., “Autonomous Robots: Modeling, Path Planning, and Control, vol. 107 (Springer Science & Business Media, 2008).Google Scholar