1. bookVolumen 16 (2022): Heft 3 (September 2022)
Zeitschriftendaten
Format
Zeitschrift
eISSN
2300-5319
Erstveröffentlichung
22 Jan 2014
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch
Uneingeschränkter Zugang

Design and Analysis of a Novel Concept-Based Unmanned Aerial Vehicle with Ground Traversing Capability

Online veröffentlicht: 16 May 2022
Volumen & Heft: Volumen 16 (2022) - Heft 3 (September 2022)
Seitenbereich: 169 - 179
Eingereicht: 26 Nov 2021
Akzeptiert: 01 Mar 2022
Zeitschriftendaten
Format
Zeitschrift
eISSN
2300-5319
Erstveröffentlichung
22 Jan 2014
Erscheinungsweise
4 Hefte pro Jahr
Sprachen
Englisch

1. Xiang H, Tian L. Development of a low-cost agricultural remote sensing system based on an autonomous unmanned aerial vehicle (UAV). Biosystems Engg. 2011;108(2):174–190.10.1016/j.biosystemseng.2010.11.010 Search in Google Scholar

2. Tahar KN, Ahmad A. A simulation study on the capabilities of rotor wing unmanned aerial vehicle in aerial terrain mapping. Int J of Phy Sci. 2012;7(8):1300–1306. Search in Google Scholar

3. Wang Z, McDonald ST. Convex relaxation for optimal rendezvous of unmanned aerial and ground vehicles, Aero Sci and Tech. 2020;99:1–19. Search in Google Scholar

4. Glida HE, Abdou L, Chelihi A, Sentouh C. Optimal model-free backstepping control for a quadrotor helicopter. Nonlin Dyna. 2020;100(4):3449–3468.10.1007/s11071-020-05671-x Search in Google Scholar

5. Labbadi M, Cherkaoui M. Novel robust super twisting integral sliding mode controller for a quadrotor under external disturbances. Int J of Dyna and Cont. 2020;8:805–815.10.1007/s40435-019-00599-6 Search in Google Scholar

6. Hassani H, Mansouri A, Ahaitouf A. Robust autonomous flight for quadrotor UAV based on adaptive nonsingular fast terminal sliding mode control. Int J of Dyna and Cont. 2021;9(2):619–635.10.1007/s40435-020-00666-3 Search in Google Scholar

7. Selma B, Chouraqui S, Abouaïssa H. Optimal trajectory tracking control of unmanned aerial vehicle using ANFIS-IPSO system. Int J of Info Techn. 2020;12(2):383–395.10.1007/s41870-020-00436-6 Search in Google Scholar

8. Elijah T, Jamisola RS, Tjiparuro Z, Namoshe M (2020). A review on control and maneuvering of cooperative fixed-wing drones. Int J of Dyna and Cont. 202;9(3):1332–1349. Search in Google Scholar

9. Heidari H, Saska M. Trajectory Planning of Quadrotor Systems for Various Objective Functions. Robo. 2021;39(1):137–152.10.1017/S0263574720000247 Search in Google Scholar

10. Abdalla M, Al-Baradie S. Real time optimal tuning of quadcopter attitude controller using particle swarm optimization, J of Eng and Techno Sci. 2020;52(5):745–764. Search in Google Scholar

11. Pinto MF, Honório LM, Marcato AL, Dantas MA, Melo AG, Capretz M, Urdiales C. ARCog: An Aerial Robotics Cognitive Architecture. Robo. 2021;39(3):483–502.10.1017/S0263574720000521 Search in Google Scholar

12. Xu H, Jiang S, Zhang A. Path Planning for Unmanned Aerial Vehicle Using a Mix-Strategy-Based Gravitational Search Algorithm. IEEE Access, 2021;9:57033–57045.10.1109/ACCESS.2021.3072796 Search in Google Scholar

13. Zhang X, Duan H. An improved constrained differential evolution algorithm for unmanned aerial vehicle global route planning. Appl Soft Comp. 2015;26:270–284.10.1016/j.asoc.2014.09.046 Search in Google Scholar

14. Roberge V, Tarbouchi M, Labonté G. Comparison of parallel genetic algorithm and particle swarm optimization for real-time UAV path planning. IEEE Trans on Indu Informat. 2012;9(1):132–141.10.1109/TII.2012.2198665 Search in Google Scholar

15. Mou C, Qing-Xian W, Chang-Sheng J. A modified ant optimization algorithm for path planning of UCAV. Appl Soft Comp. 2008;8(4):1712–1718.10.1016/j.asoc.2007.10.011 Search in Google Scholar

16. Duan H, Liu S, Wu J. Novel intelligent water drops optimization approach to single UCAV smooth trajectory planning. Aero Sci and Tech, 2009;13(8):442–449.10.1016/j.ast.2009.07.002 Search in Google Scholar

17. Silva Arantes JD, Silva Arantes MD, Motta Toledo CF, Júnior OT, Williams BC. Heuristic and genetic algorithm approaches for UAV path planning under critical situation. Int J on Art Intel Tools. 2017;26(01):1760008–1760037.10.1142/S0218213017600089 Search in Google Scholar

18. Besada-Portas E, De La Torre L, Moreno A, Risco-Martin JL. On the performance comparison of multi-objective evolutionary UAV path planners. Info Sci, 2013;238:111–125.10.1016/j.ins.2013.02.022 Search in Google Scholar

19. Cui Z, Wang Y. UAV Path Planning Based on Multi-Layer Reinforcement Learning Technique. IEEE Access. 2021;9:59486–59497.10.1109/ACCESS.2021.3073704 Search in Google Scholar

20. Yao M, Zhao M. Unmanned aerial vehicle dynamic path planning in an uncertain environment. Robo. 2015;33(3):611–621.10.1017/S0263574714000514 Search in Google Scholar

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