TIME-OPTIMAL TRAJECTORY GENERATION FOR INDUSTRIAL ROBOTS BASED ON ELITE MUTATION SPARROW SEARCH ALGORITHM

Chunyan Li,∗ Yongsheng Chao,∗ Shuai Chen,∗ Jiarong Li,∗ and Yiping Yuan∗

References

  1. [1] A. Gasparetto, P. Boscariol, and A. Lanzutti, A pathplanning and trajectory planning algorithms: A generaloverview, Mechanisms and Machine Science, 29, 2015,3–27.
  2. [2] J.J. Potter, K.L. Sorensen, and W.E. Singhose, Efficient methodfor generating pick-and-place trajectory over obstacles, In-ternational Journal of Robotics & Automation, 10(2), 2010,6–24.
  3. [3] R. Amruta, B. Deepak, B. Bibhuti, et al., Optimal trajectoryplanning of industrial robot for improving positional accuracy,Industrial Robot, 1, 2019, 71–83.
  4. [4] P.T. Zacharia, E.K. Xidias, et al., Task scheduling and motionplanning for an industrial manipulator, Robotics and Computer-Integrated Manufacturing, 29(6), 2013, 449–462.
  5. [5] 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, 309–317.8
  6. [6] T. Giulio, B. Paolo, S. Lorenzo, et al., A new path-constrainedtrajectory planning strategy for spray painting robots - rev.1,International Journal of Advanced Manufacturing Technology,98, 2018, 2287–2296.
  7. [7] L. Liu, Y. Zhu, and Q. Zha, Collaborative optimization ofrobotic spraying trajectory based on dual-population chaoticsearch particle swarm optimization algorithm, Computer Inte-grated Manufacturing Systems, 4(1), 2021, 1–21.
  8. [8] J. Huang, S. Xiao, Z.Q. Wang, et al., Research on trajectoryplanning algorithms of Cartesian space for robots, 2019 IEEE3rd Advanced Information Management, (Chong Qing, China,2019), 11–13.
  9. [9] C.S. Lin, P.R. Chang, and J.Y.S. Luh, Formulation andoptimization of cubic polynomial joint trajectories for industrialrobots, IEEE Transactions on Automatic Control, 28(12),1983, 1066–1074.
  10. [10] T. Chettibi, Smooth point-to-point trajectory planning forrobot manipulators by using radial basis functions, Robotica,37(3), 2018, 539–559.
  11. [11] Y. Pu, Y. Shi, X. Lin, et al., Interpolating industrial robotorientation with Hermite spline curve based on logarithmicquaternion, Journal of Northwestern Polytechnical University,37(06), 2019, 1165–1173.
  12. [12] J. Han, T. Gu, L. Xia, et al., Joint trajectory planningalgorithm for industrial robots based on mixed interpolation,China Mechanical Engineering, 29(12), 2018, 1460–1466.
  13. [13] T. Su, H. Zhang, Y. Wang, et al., Trajectory planning for aDelta robot based on PH curve, Robot, 40(01), 2018, 46–55.
  14. [14] J. Zhao, S. Wang, A. Jiang, et al., Trajectory planning of 6-DOFmanipulator based on Gaussian process regression method,International Journal of Robotics & Automation, 2(6), 2020,54–71.
  15. [15] Z. Long, X. Li, T. Shuai, et al., Review: Research status oftrajectory planning for industrial robots, Mechanical Scienceand Technology for Aerospace Engineering, 40(06), 2021, 853–862.
  16. [16] W. Deng, Q. Zhang, P. Liu, et al., Optimal time trajec-tory planning based on dual population genetic and chaoticoptimization algorithm, Computer Integrated ManufacturingSystems, 24(01), 2018, 101–106.
  17. [17] Y. Liu, M. Cong, H. Dong, et al. Time-optimal motion planningfor robot manipulators based on elitist genetic algorithm,International Journal of Robotics & Automation, 32(4), 2017,396–405.
  18. [18] X. Sun, D. Song, J.-z. Lin, et al., Research and implementationof trajectory planning algorithm for attacking robot on windtunnel, China Mechanical Engineering, 32(16), 2020, 1963–1971.
  19. [19] W. Wang, Q. Tao, Y. Cao, et al., Robot time-optimal trajectoryplanning based on improved cuckoo search algorithm, IEEEAccess, 8, 2020, 86923–86933.
  20. [20] A. Steinhauser and J. Swevers, An efficient iterative learningapproach to time-optimal path tracking for industrial robots,IEEE Transactions on Industrial Informatics, 14(11), 2018,5200–5207.
  21. [21] F.J. Abu-Dakka, F.J. Valero, J.L. Su Er, et al., A direct ap-proach to solving trajectory planning problems using geneticalgorithms with dynamics considerations in complex environ-ments, Robotica, 33(03), 2015, 669–683.
  22. [22] J. Wang, X. Ren, and J. Liu, Trajectory planning for multi-robot formation by one hybrid particle swarm optimizationalgorithm, International Conference on Intelligent Human-machine Systems & Cybernetics (IEEE, 2013), 344–348.
  23. [23] D. Verscheure, B. Demeulenaere, J. Swevers, et al., Time-optimal path tracking for robots: A convex optimization ap-proach, IEEE Transactions on Automatic Control AC, 54(10),2009, 2318–2327.
  24. [24] Q.B. Zhong, Z. Jie, and C.Y. Tong, Motion planning forhumanoid robot based on hybrid evolutionary algorithm, In-ternational Journal of Advanced Robotic Systems, 7(3), 2010,468–473.
  25. [25] L. Deng, X. Ma, J. Gu, et al., Artificial immune network-basedmulti-robot formation path planning with obstacle avoidance,International Journal of Robotics and Automation, 31(3),2016, 225–232.
  26. [26] Y. Li, S. Wang, Q. Chen, et al., Comparative studyof several new swarm intelligence optimization algorithms,Computer Engineering and Applications, 56(22), 2020,1–12.
  27. [27] J. Xue and B. Shen, A novel swarm intelligence optimiza-tion approach: Sparrow search algorithm, Systems Science& Control Engineering An Open Access Journal, 8(1), 2020,22-34.
  28. [28] D. Chen, S. Li, and J. Wang, Method of multi-objectivetrajectory planning of parallel mechanism based on the kine-matics, Journal of Mechanical Engineering, 55(15), 2019,163–173.
  29. [29] H.R. Tizhoosh, Opposition-based learning: A new schemefor machine intelligence, International Conference on Interna-tional Conference on Computational Intelligence for Modelling,(Vienna, Austria, 2005), 695–701.
  30. [30] K.T. Lan and C.H. Lan, Notes on the distinction of Gaussianand Cauchy mutations, Eighth International Conference on In-telligent Systems Design & Applications, (Kaohsuing, Taiwan,2008), 26–28.

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