RESEARCH ON PATH PLANNING OF LOGISTICS INTELLIGENT UNMANNED AERIAL VEHICLE, 450-463.

Hai-Wu Lee, Shoaib Ahmed, and Chi-Shiuan Lee

References

  1. [1] N.H. Motlagh, T. Taleb, and O. Arouk, Low-altitude unmannedaerial vehicles-based internet of things services: Comprehensivesurvey and future perspectives, IEEE Internet Things J., 3(6),2016, 899–922.
  2. [2] I. Bisio, C. Garibotto, and F. Lavagetto, A. Sciarrone, andS. Zappatore, Blind detection: Advanced techniques for WiFi-based drone surveillance, IEEE Transactions on VehicularTechnology, 68(1), 2019, 938–946.
  3. [3] L. Zhu, D. Yin, L. Shen, X. Xiang, and G. Bai,Research on urban application-oriented route planning ofUAV based on mobile communication network, Proc. 20154th International Conf. on Computer Science and NetworkTechnology (ICCSNT), Harbin, 2015, 1562–1570
  4. [4] X. Hu, H. Ma, Q. Ye, and H. Luo, Hierarchical method of taskassignment for multiple cooperating UAV teams, Journal ofSystems Engineering and Electronics, 26(5), 2015, 1000–1009.
  5. [5] F. Zheng, F. Wang, J. Wu, and X. Zheng, A methodology ofUAV route planning for fast image mosaicking, Proc. 2015 23rdInternational Conf. on Geoinformatics, Wuhan, 2015, 1–5.
  6. [6] Z. He and L. Zhao, The comparison of four UAV path planningalgorithms based on geometry search algorithm, Proc. 2017 9thInternational Conf. on Intelligent Human-Machine Systemsand Cybernetics (IHMSC), Hangzhou, 2017, 33–36.
  7. [7] J. Wang, Y. Sun, Z. Liu, P. Yang, and T. Lin, Route planningbased on FLOYD algorithm for intelligence transportationsystem, Proc. 2007 IEEE International Conf. on IntegrationTechnology, Shenzhen, 2007, 544–546.
  8. [8] L. Yang, D. Li, and R. Tan, Research on the shortest pathsolution method of interval valued neutrosophic graphs based onthe ant colony algorithm, IEEE Access, 8, 2020, 88717–88728.
  9. [9] L. Wang and Y. Li, A multi-objective optimization methodbased on dimensionality reduction mapping for path planningof a HALE UAV, Proc. 2019 Chinese Automation Congress(CAC), Hangzhou, China, 2019, 3189–3194.
  10. [10] Z. Lv, L. Yang, Y. He, Z. Liu, and Z. Han, 3D environmentmodeling with height dimension reduction and path planningfor UAV, Proc. 2017 9th International Conf. on Modelling,Identification and Control (ICMIC), Kunming, 2017, 734–739.
  11. [11] J. Chen, M. Li, Z. Yuan, and Q. Gu, An improved Aalgorithm for UAV path planning problems, Proc. 2020IEEE 4th Information Technology, Networking, Electronic andAutomation Control Conf. (ITNEC), Chongqing, China, 2020,958–962.
  12. [12] D.M. Xavier, N.B.F. Silva, and K.R.L.J.C. Branco, Path-following algorithms comparison using Software-in-the-Loopsimulations for UAVs, Proc. 2019 IEEE Symposium onComputers and Communications (ISCC), Barcelona, Spain,2019, 1216–1221.
  13. [13] Z. Yi, Y. Xiuxia, and Z. Weiwei, Flyable path planning formultiple UAVs in complicated threat environment, Proc. 2014International Conf. on Multisensor Fusion and InformationIntegration for Intelligent Systems (MFI), Beijing, 2014, 1–5.
  14. [14] G. Che, L. Liu, and Z. Yu, An improved ant colony optimizationalgorithm based on particle swarm optimization algorithm462for path planning of autonomous underwater vehicle, Journalof Ambient Intelligence and Humanized Computing, 11,2020,3349–3354.
  15. [15] H. Duan and P. Li, Bio-inspired computation in unmannedaerial vehicles (Berlin, Germany: Springer-Verlag, 2014).
  16. [16] H. Duan, P. Li, Y. Shi, X. Zhang, and C. Sun, Interactivelearning environment for bio-inspired optimization algorithmsfor UAV path planning, IEEE Transactions on Education,58(4), 2015, 276–281.
  17. [17] W. He, T. Wang, X. He, L.-J. Yang, and O. Kaynak, Dynamicalmodeling and boundary vibration control of a rigid-flexible wingsystem, IEEE/ASME Transactions on Mechatronics, 25(6),2020, 2711–2721.
  18. [18] D. Zhang, X. You, S. Liu, and K. Yang, Multi-colony ant colonyoptimization based on generalized jaccard similarity recom-mendation strategy, IEEE Access, 7, 2019, 157303–157317.
  19. [19] M.M. Alobaedy, A.A. Khalaf, and I.D. Muraina, Analysis ofthe number of ants in ant colony system algorithm, Proc. 20175th International Conf. on Information and CommunicationTechnology (ICoIC7), Malacca City, 2017, 1–5.
  20. [20] W. Zheng, X. Jin, F. Deng, S. Mao, Y. Qu, Y. Yang, X. Li,S. Long, C. Zheng, and Z. Xie, Database query optimizationbased on parallel ant colony algorithm, Proc. 2018 IEEE 3rdInternational Conf. on Image, Vision and Computing (ICIVC),Chongqing, 2018, 653–656.
  21. [21] Q. Yang and S. Yoo, Optimal UAV path planning: sensingdata acquisition over IoT sensor networks using multi-objectivebio-inspired algorithms, IEEE Access, 6, 2018, 13671–13684.
  22. [22] A. Mohamed, S. Watkins, R. Clothier, M. Abdulrahim, K.Massey, and R. Sabatini, Fixed-wing MAV attitude stabilityin atmospheric turbulence—Part 2: Investigating biologically-inspired sensors, Progress in Aerospace Sciences, 71, 2014,1–13.
  23. [23] M. Euston, P. Coote, R. Mahony, J. Kim, and T. Hamel, Acomplementary filter for attitude estimation of a fixed-wingUAV, Proc. IEEE/RSJ International Conf. on IntelligentRobots and Systems (IROS), Nice, 2008, 340–345.
  24. [24] P. Poksawat, L. Wang, and A. Mohamed, Gain scheduledattitude control of fixed-wing UAV with automatic controllertuning, IEEE Transactions on Control Systems Technology,26(4), 2018, 1192–1203.
  25. [25] G. Fink, H. Xie, A.F. Lynch, and M. Jagersand, Nonlineardynamic image-based visual servoing of a quadrotor, Journalof Unmanned Vehicle Systems, 3(1), 2015, 1–21.
  26. [26] M. Burger and M. Guay, A backstepping approach tomultivariable robust constraint satisfaction with applicationto a VTOL helicopter, Proc. 48th IEEE. Decision Control,Shanghai, China, 2009, 5239–5244.
  27. [27] N. Cao and A.F. Lynch, Inner–outer loop control for quadrotorUAVs with input and state constraints, IEEE Transactions onControl Systems Technology, 24(5), 2016, 1797–1804.
  28. [28] W. He, X. Mu, L. Zhang, and Y. Zou, Modeling andtrajectory tracking control for flapping-wing micro aerialvehicles, IEEE/CAA Journal of Automatica Sinica, 8(1), 2021,148–156.
  29. [29] G.F. Che and Z. Yu, Neural-network estimators based fault-tolerant tracking control for AUV via ADP with rudders faultsand ocean current disturbance, Neurocomputing, 411, 2020,442–454.
  30. [30] G.F. Che, Single critic network based fault-tolerant trackingcontrol for underactuated AUV with actuator fault, OceanEngineering, 254, 2022, 111380.
  31. [31] Z. Chen, D. Yin, D. Chen, M. Pan, and J. Lai, Wifi-based UAVcommunication and monitoring system in regional inspection,Proc. 2018 International Computers, Signals and SystemsConf. (ICOMSSC), Dalian, China, 2018, 386–392.
  32. [32] M. Itani, A. Haroun, and W. Fahs, “Obstacle avoidancefor ultrasonic unmanned aerial vehicle monitoring usingandroid application, Proc. 2018 International Arab Conf. onInformation Technology (ACIT), Werdanye, Lebanon, 2018,1–4.
  33. [33] H.-W. Lee, Y. Zhu, X. Shi, F.-F. Peng, and W.-J. Jin, Researchof four-axis aircraft using WIFI and rotary anti-collision system,Proc. 2018 IEEE International Conf. on Applied SystemInvention (ICASI), Chiba, 2018, 665–668.
  34. [34] H. Jing-Lin, S. Xiu-Xia, L. Ri, D. Xiong-Feng, andL. Mao-Long, UAV real-time route planning based onmulti-optimized RRT algorithm, Proc. 2017 29th ChineseControl and Decision Conf. (CCDC), Chongqing, 2017,837–842.
  35. [35] H. Jun and Z. Qingbao, Multi-objective mobile robot pathplanning based on improved genetic algorithm, Proc. 2010International Conf. on Intelligent Computation Technologyand Automation, Changsha, 2010, 752–756.

Important Links:

Go Back