TRAJECTORY OPTIMIZATION OF A SPOT-WELDING ROBOT IN THE JOINT AND CARTESIAN SPACES, 109-125.

Ehsan Sharafian Moghaddam, Maryam Ghassabzadeh Saryazdi and Afshin Taghvaeipour

References

  1. [1] K. Paes, et al., Energy efficient trajectories for an industrialABB robot, Procedia Cirp, 15, 2014, 105–110.
  2. [2] H.S. Lim, et al., Particle swarm optimization algorithms withselective differential evolution for AUV path planning, In-ternational Journal of Robotics and Automation, 9(2), 2020,94–112.
  3. [3] C. Hansen, et al., Enhanced approach for energy-efficient tra-jectory generation of industrial robots, in 2012 IEEE Inter-national Conference on Automation Science and Engineering(CASE) (IEEE, 2012).
  4. [4] M. Pellicciari, et al., A method for reducing the energy con-sumption of pick-and-place industrial robots, Mechatronics,23(3), 2013, 326–334.
  5. [5] A. Mohammed, et al., Minimizing energy consumption forrobot arm movement, Procedia Cirp, 25, 2014, 400–405.
  6. [6] C. Hansen, J. Kotlarski, and T. Ortmaier, Optimal motionplanning for energy efficient multi-axis applications, Interna-tional Journal of Mechatronics and Automation, 4(3), 2014,147–160.
  7. [7] P. Boscariol and D. Richiedei, Energy-efficient design of multi-point trajectories for Cartesian robots, The International Jour-nal of Advanced Manufacturing Technology, 102(5–8), 2019,1853–1870.
  8. [8] A. Fahim, M. Tetreault, and D. Necsulescu, Robot trajec-tory optimisation with dynamic constraints, The InternationalJournal of Advanced Manufacturing Technology, 3(1), 1988,71–76.16125
  9. [9] Q.-C. Pham, A general, fast, and robust implementationof the time-optimal path parameterization algorithm, IEEETransactions on Robotics, 30(6), 2014, 1533–1540.
  10. [10] Q. Zhang and M.-Y. Zhao, Minimum time path planning ofrobotic manipulator in drilling/spot welding tasks, Journal ofComputational Design and Engineering, 3(2), 2016, 132–139.
  11. [11] L. Cheng, et al., An improved PSO algorithm for time-optimaltrajectory planning of Delta robot in intelligent packaging, TheInternational Journal of Advanced Manufacturing Technology,107, 2019, 1091–1099.
  12. [12] M. Ghasemi, N. Kashiri, and M. Dardel, Time-optimal trajec-tory planning of robot manipulators in point-to-point motionusing an indirect method, Proceedings of the Institution of Me-chanical Engineers, Part C: Journal of Mechanical EngineeringScience, 226(2), 2012, 473–484.
  13. [13] S. Diao, et al., Task-level time-optimal collision avoidancetrajectory planning for grinding manipulators, Proceedings ofthe Institution of Mechanical Engineers, Part C: Journal ofMechanical Engineering Science, 233(8), 2019, 2894–2908.
  14. [14] F.J. Abu-Dakka, et al., Statistical evaluation of an evolution-ary algorithm for minimum time trajectory planning problemfor industrial robots, The International Journal of AdvancedManufacturing Technology, 89(1–4), 2017, 389–406.
  15. [15] G. Wu, W. Zhao, and X. Zhang, Optimum time-energy-jerktrajectory planning for serial robotic manipulators by repa-rameterized quintic NURBS curves, Proceedings of the Institu-tion of Mechanical Engineers, Part C: Journal of MechanicalEngineering Science, 2020, 0954406220969734.
  16. [16] H. Liu, X. Lai, and W. Wu, Time-optimal and jerk-continuoustrajectory planning for robot manipulators with kinematicconstraints, Robotics and Computer-Integrated Manufacturing,29(2), 2013, 309–317.
  17. [17] J. Huang, et al., Optimal time-jerk trajectory planning forindustrial robots, Mechanism and Machine Theory, 121, 2018,530–544.
  18. [18] R. Saravanan, S. Ramabalan, and C. Balamurugan, Evolu-tionary optimal trajectory planning for industrial robot withpayload constraints, The International Journal of AdvancedManufacturing Technology, 38(11–12), 2008, 1213–1226.
  19. [19] R. Saravanan, S. Ramabalan, and C. Balamurugan, Evolution-ary multi-criteria trajectory modeling of industrial robots inthe presence of obstacles, Engineering Applications of ArtificialIntelligence, 22(2), 2009, 329–342.
  20. [20] H. Fang, S. Ong, and A. Nee, Orientation planning of robot end-effector using augmented reality, The International Journal ofAdvanced Manufacturing Technology, 67(9–12), 2013, 2033–2049.
  21. [21] M. Chalvin, et al., Layer-by-layer generation of optimizedjoint trajectory for multi-axis robotized additive manufactur-ing of parts of revolution, Robotics and Computer-IntegratedManufacturing, 65, 2020, 101960.
  22. [22] M. Givehchi, A.H. Ng, and L. Wang, Spot-welding sequenceplanning and optimization using a hybrid rule-based approachand genetic algorithm, Robotics and Computer-Integrated Man-ufacturing, 27(4), 2011, 714–722.
  23. [23] X. Wang, et al., Double global optimum genetic algorithm–particle swarm optimization-based welding robot path plan-ning, Engineering Optimization, 48(2), 2016, 299–316.
  24. [24] A. Kov´acs, Integrated task sequencing and path planningfor robotic remote laser welding, International Journal ofProduction Research, 54(4), 2016, 1210–1224.
  25. [25] H. Yang and H. Shao, Distortion-oriented welding path opti-mization based on elastic net method and genetic algorithm,Journal of Materials Processing Technology, 209(9), 2009,4407–4412.
  26. [26] X. Wang, Y. Yan, and X. Gu, Spot welding robot pathplanning using intelligent algorithm, Journal of ManufacturingProcesses, 42, 2019, 1–10.
  27. [27] V. Beik, H. Marzbani, and R. Jazar, Welding sequence opti-misation in the automotive industry: A review, Proceedings ofthe Institution of Mechanical Engineers, Part C: Journal ofMechanical Engineering Science, 233(17), 2019, 5945–5952.
  28. [28] X. Wang, et al., A survey of welding robot intelligent pathoptimization, Journal of Manufacturing Processes, 63, 2020,14–23.
  29. [29] K.S. Fu, R. Gonzalez, and C.G. Lee, Robotics: Control Sensing.Vis. (Tata McGraw-Hill Education, 1987).
  30. [30] J.J. Craig, Introduction to Robotics: Mechanics and Control,3rd edition (Pearson Education India, 2009).
  31. [31] J. Angeles, Fundamentals of Robotic Mechanical Systems(Springer, 2002).
  32. [32] E. Sharafian, A. Taghvaeipour, and M. Ghassabzadeh, Revis-iting screw theory-based approaches in the constraint wrenchanalysis of robotic systems, Robotica, 40(5), 2022, 1406–1430.
  33. [33] S.S. Rao, Engineering Optimization: Theory and Practice(John Wiley & Sons, 2019).
  34. [34] A. Azarfar, Self-tuning fuzzy task space controller for puma560 robot, International Journal of Robotics and Automation(IJRA), 7(4), 2018, 273–282.
  35. [35] M. Mihola, Z. Zeman, and D. Fojtik, Automation of thedesign of the cross-section of the manipulator arms profile,International Journal of Robotics and Automation (IRJA),10(3), 2021, 170.

Important Links:

Go Back