Yuehao Yan, Zhiying Lv, Jinbiao Yuan, and Shufeng Zhang


  1. [1] M. DeGarmo, and G.M. Nelson, Prospective unmanned aerialvehicle operations in the future national airspace system,Proceedings of the 4th Aviation Technology, Integration andOperations (ATIO) Forum, AIAA, Chicago, IL, 2004, 20–22.
  2. [2] Y. Yan, Z. Lv, and R. Zhang, Fault evaluation of unmannedaerial vehicles power system with an improved fuzzy multi-ple attribute group decision-making, International Journal ofRobotics and Automation, 33(3), 2018, 284–292.
  3. [3] L.E. Parker, Current state of the future of air in distributedautonomous mobile robotics, Distributed Autonomous RoboticSystems, 4, 2000, 3–12.
  4. [4] A.D.J. Caves, Human-automation collaborative RRT for UAVmission path planning (Cambridge, MA: Massachusetts Insti-tute of Technology, 2010).
  5. [5] Y. Chen, X. Zhao, and J. Han, Review of 3D path planningmethods for mobile robot, Robot, 32, 2010, 568–576.
  6. [6] C. Zheng, Evolutionary route planner for unmanned air ve-hicles, IEEE Transactions on Robotics, August 21(4), 2005,609–620.
  7. [7] W. Ye, D.W. Ma, and H.D. Fan, Algorithm for low alti-tude penetration aircraft path planning with improved antcolony algorithm, Chinese Journal of Aeronautics, 18(4), 2005,304–309.
  8. [8] Z. Liu, J.G. Shi, and X.G. Gao, Application of Voronoi diagramin flight path planning, Acta Aeronautica et AstronauticaSinica, 29, 2008, 16–18 [in Chinese].
  9. [9] N.D. Richards, M. Sharma, and D.G. Ward, A hybridA/automaton approach to on-line path planning with obsta-cle avoidance, Proceedings of AIAA 1st Intelligent SystemsTechnical Conference, Chicago, IL, USA, AIAA-2004-6229,2004.
  10. [10] Y. Kim, D.W. Gu, and I. Postlethwaite, Real-time pathplanning with limited information for autonomous unmannedair vehicles, Automatica, 44(3), 2008, 696–712.
  11. [11] C.L. Bottasso, D. Leonello, and B. Savini, Path planning forautonomous vehicles by trajectory smoothing using motionprimitives, IEEE Transactions on Control Systems Technology,16(6), 2008, 1152–1168.
  12. [12] O. Khatib, Real time obstacle avoidance for manipulators andmobile robots, The international Journal of Robotics Research,5, 1986, 90–96.
  13. [13] E. Oland, and R. Kristiansen, Collision and terrain avoidancefor UAVs using the potential field method, IEEE AerospaceConference, Washington, 1986, 1–7.
  14. [14] J.Y. Liu, Z.Q. Guo, and S.Y. Liu, The simulation of the UAVcollision avoidance based on the artificial potential field method,Advanced Materials Research, 591–593, 2012, 1400–1404.
  15. [15] A. Benghezal, R. Louali, A. Bazoula, and T. Chettibi, Tra-jectory generation for a fixed-wing UAV by the potential fieldmethod, Proc. of 3rd CEIT, Tlemcen, Algeria, 2015, 1–6.
  16. [16] D. McIntyre, W. Naeem, and X. Xu, Cooperative obstacleavoidance using bidirectional artificial potential fields, Proc.11th UKACC Control, Belfast, United Kingdom, 2016, 1–6.
  17. [17] Y.B. Chen, G.C. Luo, Y.S. Mei, J.Q. Yu, and X.L. Su, UAVpath planning using artificial potential field method updatedby optimal control theory, International Journal of SystemsScience, 45(6), 2014, 1407–1420.
  18. [18] Z.Y. Lv, A fuzzy multiple attribute decision making methodbased on possibility degree, Journal of Intelligent & FuzzySystems, 31, 2016, 787–794.
  19. [19] Z.Y. Lv, T.M. Huang, and X.Z. Liang, A method for fuzzymulti-attribute decision-making with preference to attribute,CAAI Transactions on Intelligent Systems, 10(2), 2015, 227–233 (in Chinese).
  20. [20] Y.Y. Yao, Three way granular computing, rough sets, andformal concept analysis, International Journal of ApproximateReasoning, 116, 2020, 106–125.
  21. [21] X.Y. Zhang, X. Tang, J.L. Yang, and Z.Y. Lv, Quantita-tive three-way class-specific attribute reducts based on regionpreservations, International Journal of Approximate Reason-ing, 117, 2020, 96–121.
  22. [22] X.Y. Zhang, and D.Q. Miao, Three-way attribute reducts,International Journal of Approximate Reasoning, 88, 2017,401–434.
  23. [23] C. Jiang, D. Guo, Y. Duan, and Y. Liu, Strategy selectionunder entropy measures in movement-based three way decision,International Journal of Approximate Reasoning, 119, 2020,280–291
  24. [24] H. Yu, L.Y. Chen, J.T. Yao, and X.N. Wang, A three-wayclustering method based on an improved DBSCAN algorithm,Physica A: Statistical Mechanics and Its Applications, 535,2019, 1–14.6

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