Distributed Autonomous Robotic Systems 6 pp 221-230 | Cite as
Multiple UAV cooperative searching operation using polygon area decomposition and efficient coverage algorithms
Abstract
This paper focuses on the problem of cooperatively searching a given area to detect objects of interest, using a team of heterogenous unmanned air vehicles (UAVs). The paper presents algorithms to divide the whole area taking into account UAV’s relative capabilities and initial locations. Resulting areas are assigned among the UAVs, who could cover them using a zigzag pattern. Each UAV has to compute the sweep direction which minimizes the number of turns needed along a zigzag pattern. Algorithms are developed considering their computational complexity in order to allow near-real time operation. Results demonstrating the feasibility of the cooperative search in a scenario of the COMETS multi-UAV project are presented.
Keywords
Path Planning Convex Polygon Zigzag Pattern Sweep Direction Relative CapabilityPreview
Unable to display preview. Download preview PDF.
References
- 1.Alami R, Robert F, Ingrand F, Suzuki S (1995) Multi-robot cooperation through incremental plan-merging. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2573–2579. Nagoya, JapanGoogle Scholar
- 2.Barcala M, Rodriguez A (1998) Helicopteros. EUIT Aeronautica, MadridGoogle Scholar
- 3.Beard R W, McLain T W, Goodrich M (2002) Coordinated target assignment and intercept for unmanned air vehicles. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2581–2586. WashingtonGoogle Scholar
- 4.Bellingham J, Tillerson M, Richards A, How J P (2001) Multi-task allocation and path planning for cooperating UAVs. In: Cooperative Control: Models, Applications and Algorithms, pp. 1–19, Conference on Coordination, Control and Optimization.Google Scholar
- 5.Butler Z J, Rizzi A A, Hollis R L(2000) Cooperative coverage of rectilinear environments. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2722–2727. San Francisco, CAGoogle Scholar
- 6.Chandler P R, Pachter M, Swaroop D, Fowler J M, Howlett J K, Rasmussen S, Schumacher C, Nygard K (2002) Complexity in UAV cooperative control. In: Proceedings of the American Control Conference. Anchorage, AKGoogle Scholar
- 7.Computational Geometry Algorithms Library (CGAL). Web address: http://www.egal.org/Google Scholar
- 8.Giulietti F, Pollini L, Innocenti M (2000) Autonomous formation flight. IEEE Control Systems Magazine 20:34–44CrossRefGoogle Scholar
- 9.Hert S, Lumelsky V (1998) Polygon area decomposition for multiple-robot workspace division. International Journal of Computational Geometry and Applications, 8(4):437–466.MATHCrossRefMathSciNetGoogle Scholar
- 10.Luo C., Yang S X, Stacey D A, Jofriet J C (2002) A solution to vicinity problem of obstacles in complete coverage path planning. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 612–617. Washington DCGoogle Scholar
- 11.McLain T, Beard R (2000) Cooperative rendezvous of multiple unmanned air vehicles. In: Proceedings of the AIAA Guidance, Navigation and Control Conference, paper no. AIAA 2000-4369. Denver, COGoogle Scholar
- 12.Pachter M, D’Azzo J J, Proud A W (2001) Tight formation flight control. AIAA Journal of Guidance, Control and Dynamics 24:246–254CrossRefGoogle Scholar
- 13.Pledgie S T, Hao Y, Ferreira A M, Agrawal S K, Murphey R (2002) Groups of unmanned vehicles: Differential flatness, trajectory planning, and control. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 3461–3466. Washington DCGoogle Scholar
- 14.Wesley H., Huang W H (2001) Optimal line-sweep-based decompositions for coverage algorithms. In: Proceedings of the 2001 IEEE International Conference on Robotics and Automation, 1:27–32. Seoul, KoreaGoogle Scholar