Wangbao Xu and Mingyan Sun


  1. [1] Y.H. Yang, W.B. Xu, G.X. Rong, X. Liu, and X. Chen, A self-organizing approach based on task-points for forming complexswarm-robot transport formations, International Journal ofRobotics and Automation, 32(5), 2017, 482–491.
  2. [2] W.B. Xu, X.P. Liu, X.B. Chen, and Q.B. Sun, An artificialmoment method for conflict resolutions with robots being closeto their targets, Information Sciences, 542, 2021, 286–301.
  3. [3] M.S. Abed, O.F. Lutfy, and Q.F. Al-Doori, A review onpath planning algorithms for mobile robots, Engineering andTechnology Journal, Part A, 39(5), 2021, 804–820.
  4. [4] Y. Gao, J. Liu, M.Q. Hu, H. Xu, K.P. Li, and H. Hu,A new path evaluation method for path planning withlocalizability, IEEE Access, 7, 2019, 162583–162597. DOI:10.1109/access.2019.2950725.
  5. [5] D. Devaurs, T. Sim´eon, and J. Cort´es, Optimal path planningin complex cost spaces with sampling-based algorithms, IEEETransactions on Automation Science and Engineering, 13(2),2016, 415–424.
  6. [6] T.T. Mac, C. Copot, D.T. Tran, and R. De Keyser, Heuristicapproaches in robot path planning: A survey, Robotics andAutonomous Systems, 86, 2016, 13–28.
  7. [7] W.-B. Xu, X.-B. Chen, J. Zhao, and X.-P. Liu, Function-segment artificial moment method for sensor-based pathplanning of single robot in complex environments, InformationSciences, 280, 2014, 64–81.
  8. [8] A.K. Guruji, H. Agarwal, and D.K. Parsediya, Time-efficientA algorithm for robot path planning, Procedia Technology,23(1), 2016, 144–149.
  9. [9] M.M. Zafar, M.L. Anjum, and W. Hussain, LTA: Local tangentbased A for optimal path planning, Autonomous Robots, 45,2021, 209–227.
  10. [10] M. Dakulovi´c and I. Petrovi´c, Two-way D algorithm for pathplanning and replanning, Robotics and Autonomous Systems,59(5), 2011, 329–342.
  11. [11] C.-B. Moon and W. Chung, Kinodynamic planner dual-treeRRT (DT-RRT) for two-wheeled mobile robots using therapidly exploring random tree, IEEE Transactions on IndustrialElectronics, 62(2), 2015, 1080–1090.
  12. [12] K. Wei and B.Y. Ren, A method on dynamic path planning forrobotic manipulator autonomous obstacle avoidance based onan improved RRT algorithm, Sensors, 18(2), 2018, 571. DOI:10.3390/s18020571.
  13. [13] F. Kiani, A. Seyyedabbasi, R. Aliyev, M.U. Gulle, H. Basyildiz,and M.A. Shah, Adapted-RRT: Novel hybrid method tosolve three-dimensional path planning problem using samplingand metaheuristic-based algorithms, Neural Computing andApplications, 33, 2021, 15569–15599.
  14. [14] X. Chen, Y.Y. Kong, X. Fang, and Q. Wu, A fast two-stageACO algorithm for robotic path planning, Neural Computingand Applications, 22, 2013, 313–319.
  15. [15] M.K. Singh and D.R. Parhi, Path optimisation of a mobilerobot using an artificial neural network controller, InternationalJournal of Systems Science, 42(1), 2011, 107–120.
  16. [16] V. Jamshidi, V. Nekoukar, and M.H. Refan, Real timeUAV path planning by parallel grey wolf optimization withalign coefficient on CAN bus, Cluster Computing, 24, 2021,2495–2509.
  17. [17] O. Montiel, R. Sep´ulveda, and U. Orozco-Rosas, Optimalpath planning generation for mobile robots using parallelevolutionary artificial potential field, Journal of Intelligent &Robotic Systems, 79(2), 2015, 237–257.
  18. [18] D. Fox, W. Burgard, and S. Thrun, The dynamic windowapproach to collision avoidance, IEEE Robotics & AutomationMagazine, 4(1), 1997, 23–33.
  19. [19] A. Babinec, F. Duchoˇn, M. Dekan, Z. Mikulov´a, and L.Juriˇsica, Vector field histogram with look-ahead tree extensiondependent on time variable environment, Transactions of theInstitute of Measure and Control, 40(4), 2016, 1250–1264.
  20. [20] L.C. Wang, L.S. Yong, and M.H. Ang Jr., Hybrid of globalpath planning and local navigation implemented on a mobilerobot in indoor environment, Proc. IEEE Int. Symposiumon Intelligent Control, Vancouver, BC, 2002, 821–826. DOI:10.1109/ISIC.2002.1157868.
  21. [21] X.B. Zhang, J.R. Wang, Y.C. Fang, and J. Yuan, Multilevelhumanlike motion planning for mobile robots in complex indoorenvironments, IEEE Transactions on Automation Science andEngineering, 16(3), 2019, 1244–1258.
  22. [22] K.N. McGuire, G.C.H.E. de Croon, and K. Tuyls, Acomparative study of bug algorithms for robot navigation,Robotics and Autonomous Systems, 121, 2019, 103261.
  23. [23] W.-B. Xu, X.-P. Liu, X.B. Chen, and J. Zhao, Improvedartificial moment method for decentralized local path planningof multirobots, IEEE Transactions on Control SystemsTechnology, 23(6), 2015, 2383–2390.

Important Links:

Go Back