Hostname: page-component-848d4c4894-cjp7w Total loading time: 0 Render date: 2024-06-20T19:40:19.188Z Has data issue: false hasContentIssue false

Path Planning of Complex Pipe Joints Welding with Redundant Robotic Systems

Published online by Cambridge University Press:  11 February 2019

H. Ghariblu*
Mechanical Engineering Department, University of Zanjan, Zanjan, Iran E-mail:
M. Shahabi
Mechanical Engineering Department, University of Zanjan, Zanjan, Iran E-mail:
*Corresponding author. E-mail:


In this paper, a path planning algorithm for robotic systems with excess degrees of freedom (DOF) for welding of intersecting pipes is presented. At first step, the procedure of solving the inverse kinematics considering system kinematic redundancy is developed. The robotic system consists of a 6 DOF robotic manipulator installed on a railed base with linear motion. Simultaneously, the main pipe is able to rotate about its longitudinal axis. The system redundancy is employed to improve weld quality. Three different simulation studies are performed to show the effect of the robotic system kinematic redundancy to plan a better path for the welding of intersecting pipes. In the first case, it is assumed that robotic manipulator base and main pipe are fixed, and the path is planned only with manipulator joints motion. In the second case, only the robot base is free to move and the main pipe is fixed, and in the third case, the main pipe is free to rotate together with the base of the manipulator. It is seen that kinematic constraints according to the system’s redundancy will help to plan the most efficient path for the welding of complex pipe joints.

Copyright © Cambridge University Press 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)


Ruiz, A. G., Santos, J. C., Croes, J., Desmet, W. and da Silva, M. M., “On redundancy resolution and energy consumption of kinematically redundant planar parallel manipulators,” Robotica 36(6), 809821 (2018).CrossRefGoogle Scholar
Guo, D., Li, K. and Liao, B., “Bi-criteria minimization with MWVN-INAM type for motion planning and control of redundant robot manipulators,” Robotica 36(5), 655675 (2018).CrossRefGoogle Scholar
Hwang, S., Kim, H., Choi, Y., Shin, K. and Han, C, “Design optimization method for 7 DOF robot manipulator using performance indices,” Int. J. Precis. Eng. Manuf. 18(3), 293299 (2017).CrossRefGoogle Scholar
Huang, Y. and Fei, M., “Motion planning of robot manipulator based on improved NSGA-II,” Int. J. Control, Autom. Syst. 16(4), 18781886 (2018).CrossRefGoogle Scholar
Chembuly, V. S. and Voruganti, H. K., “Trajectory planning of redundant manipulators moving along constrained path and avoiding obstacles,” Procedia Comput. Sci. 133, 627634 (2018).CrossRefGoogle Scholar
Léger, J. and Angeles, J., “Off-line programming of six-axis robots for optimum five-dimensional tasks,” Mech. Mach. Theory 100, 155169 (2016).CrossRefGoogle Scholar
Meghdari, A., Naderi, D. and Eslami, S., “Optimal stability of a redundant mobile manipulator via genetic algorithm,” Robotica 24(6), 739743 (2006).CrossRefGoogle Scholar
Atawnih, A., Papageorgiou, D. and Doulgeri, Z., “Kinematic control of redundant robots with guaranteed joint limit avoidance,” Robot. Auton. Syst. 79, 122131 (2016).CrossRefGoogle Scholar
Korayem, M. H. and Ghariblu, H., “Maximum allowable load on wheeled mobile manipulators imposing redundancy constraints,” Robot. Auton. Syst. 44(2), 151159 (2003).CrossRefGoogle Scholar
Lu, Y., Tian, X. and Liang, J., “Track control in automated welding of saddle curve,” J. Sci. Ind. Res. 69(11), 811817 (2010).Google Scholar
Chen, C., Hu, S., He, D. and Shen, J., “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), 4148 (2013).CrossRefGoogle Scholar
Liu, Y., Zhao, J., Lu, Z. and Chen, S., “Pose planning for the end-effector of robot in the welding of intersecting pipes,” Chin. J. Mech. Eng.-English Ed. 24(2), 264 (2011).CrossRefGoogle Scholar
Wu, L., Cui, K. and Chen, S.-B., “Redundancy coordination of multiple robotic devices for welding through genetic algorithm,” Robotica 18(6), 669676 (2000).CrossRefGoogle Scholar
Ren, F., Chen, S. J., Yin, S. Y. and Guan, X. Y., “Modeling on weld position and welding torch pose in welding of intersected pipes,” Trans. China Weld. Ins. 29(11), 3336 (2008).Google Scholar
Yao, T., Gai, Y. and Liu, H., “Development of a robot system for pipe welding,” In: 2010 International Conference on Measuring Technology and Mechatronics Automation, Changsha, China (IEEE, 2010 March).CrossRefGoogle Scholar
Tian, X. C. and , Y., “Trajectory control in automated welding of tubular joints,” In Applied Mechanics and Materials (Du, Z. and Liu, B., eds.) (Trans Tech Publ, Switzerland, 2010).Google Scholar
Doan, N. C. N. and Lin, W., “Optimal robot placement with consideration of redundancy problem for wrist-partitioned 6R articulated robots,” Robot. Comput.-Integr. Manuf. 48, 233242 (2017).CrossRefGoogle Scholar
Shi, L. and Tian, X., “Automation of main pipe-rotating welding scheme for intersecting pipes,” Int. J. Adv. Manuf. Technol. 77(5–8), 955964 (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), 20992107 (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
Huo, L. and Baron, L., “The self-adaptation of weights for joint-limits and singularity avoidances of functionally redundant robotic-task,” Robot. Comput.-Integr. Manuf. 27(2), 367376 (2011).CrossRefGoogle Scholar
Fahimi, F., Autonomous Robots: Modeling, Path Planning, and Control (Springer Science & Business Media, Berlin/Heidelberg, Germany, 2008), Vol. 107.Google Scholar