Survey of Cooperative Path Planning for Multiple Unmanned Aerial Vehicles

Article Preview

Abstract:

As an important part of cooperative control for multiple unmanned aerial vehicles (UAVs), cooperative path planning can get optimal flight path which can satisfy different constraints. Research on cooperative path planning for multiple UAVs is summarized in this paper. Firstly, problem description and constraints are given. Then, solution frameworks and path coordination approaches are summarized. After that, several control methods commonly used in formation of multiple UAVs are introduced respectively. Lastly, possible research directions in the future time are put forward.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

388-393

Citation:

Online since:

October 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Wen Ye, Hongda Fan, Aihong Zhu, et al. Mission planning for Unmanned Aerial Vehicles [M]. Beijing: National Defense Industry Press, 2011. 171 – 172. (In Chinese).

Google Scholar

[2] Borrelli F, Subramanian D, Raghunathan U A, et al. MILP and NLP Techniques for Centralized Trajectory Planning of Multiple Unmanned Air Vehicles [C]. In Proceedings of the 2006 American Control Conference. 2006, 6: 5763–5768.

DOI: 10.1109/acc.2006.1657644

Google Scholar

[3] Shaomei Song, Ke Zhang, Shiyi Guan. A Trajectory Planning Method Based on Hierarchy Decomposition Strategy for Coordination of Multiple Unmanned Air Vehicles. [J]. Tactical Missile Technology, 2004, (1): 44–48. (In Chinese).

Google Scholar

[4] Li Yang. Research on Path Planning for Unmanned Aerial Vehicle [D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2009. (In Chinese).

Google Scholar

[5] Richards A, How J P. Decentralized Model Predictive Control of Cooperating UAVs [C]. In Proceedings of the 43rd IEEE Conference on Control and Decision. 2004, 4: 4286–4291.

DOI: 10.1109/cdc.2004.1429425

Google Scholar

[6] La Velle S M. Rapidly-Exploring Random Trees: A New Tool for Path Planning [R]. Computer Science Department, Iowa State University, (1998).

Google Scholar

[7] Yong BAO, Xiaowei FU, Xiaoguang GAO. A Method of Cooperative Path Planning of Multiple UAVs on Potential Field Theory [J]. Fire Control& Command Control, 2012, 37(3): 10-12. (In Chinese).

Google Scholar

[8] Feng Zhang, Zhe Sun, Meiju Liu. Formation Control based on the method of artificial potential and the leader-follower for multiple mobile robots [J]. Journal of Shenyang Jianzhu University, 2010, 26(4): 803–807. (In Chinese).

Google Scholar

[9] Campa G, Napolitano M R, Brad S, et al. Design of Control Laws for Maneuvered Formation Flight [C]. Proceedings of the American Control Conference. Boston, USA: IEEE, 2004: 2344–2349.

DOI: 10.23919/acc.2004.1383814

Google Scholar

[10] Xiaoli Li, Jin Xie. An improved artificial potential field method used in multiple robots collision planning [J]. Computer engineering and Applications, 2005, 17: 56–58. (In Chinese).

Google Scholar

[11] Desai J P. A graph theoretic approach for modeling mobile robot team formations [J]. J of Robotic Systems, 2002, 19(11): 511–525.

DOI: 10.1002/rob.10057

Google Scholar

[12] Pereira G A S, Das A K, Kumar V, et al. Formation control with configuration space constraints [C]. Proc of the IEEE/RJS Int Confon Intelligent Robots and Systems. Las Vegas, (2003).

Google Scholar

[13] Olfati-Saber R, Murray R M. Graph rigidity and distributed formation stabilization of multi-vehicle systems [C]. Las Vegas: 41st Conference on Decision and Control, (2002).

DOI: 10.1109/cdc.2002.1184307

Google Scholar