Abstract
The study of unmanned aerial systems (UAS) has been an active research topic in recent years due to the rapid growth of UAS real-world applications driven by the Global War on Terrorism (GWOT). UAS are defined as a complete unmanned system including control station, data links, and vehicle. Unmanned aerial vehicle (UAV) refers to the vehicle element of the UAS. Currently UAS operate standalone, independent of neighboring UAS and used primarily for reconnaissance. However UAS roles are expanding to the point where UAV swarms will operate as cooperative autonomous units. The reason is that cooperatively controlled multiple UAS have the potential to complete mission critical complicated tasks with the higher efficiency and failure tolerance, such as coordinated navigation to a target, coordinated terrain exploration and search and rescue operations.
This chapter presents study results associated with real-time trajectory planning and cooperative formation flying algorithms for use in performing multi-UAV cooperative operations. Closed form analytical and simulation results were used along with a UAS simulation test bed for evaluating and verifying these algorithms in multi-UAV cooperative scenarios. The full kinematics constraints of the UAV model is explicitly used, ensuring the planned trajectories and formations are feasible. Two operational modes are implemented for every UAV, one corresponding to the search phase, the other corresponding to the cooperative flying phase. Each phase is executed upon receiving commands. Finally this chapter discusses the use of this simulation environment for multi-UAV cooperative operator training.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chuang, J.-H.: Potential-based modeling of three-dimensional workspace for obstacle avoidance. IEEE Trans. on Robotics and Automation 14, 778–785 (1998)
Kyriakopoulos, K.J., Kakambouras, P., Krikelis, N.J.: Potential fields for nonholomic vehicles. In: Proceedings of the IEEE International Symposium, pp. 461–465. IEEE Computer Society Press, Los Alamitos (1995)
Judd, K.B., Mclain, T.W.: Spline based path planning for unmanned air vehicles. In: AIAA Guidance, Navigation, and Control Conference and Exhibit, vol. AIAA-2001-4238, Montreal, Canada (Aug. 2001)
Nilsson, N.J.: Principles of Artificial Intelligence. Tioga Publishing Company (1980)
Stentz, A.: Optimal and efficient path planning for partially-known environments. In: IEEE International Conference on Robotics and Automation (May 1994)
Stentz, A.: The Focussed D* Algorithm for Real-Time Replanning. In: Proceedings of the International Joint Conference on Artificial Intelligence (August 1995)
Qu, Z., Wang, J., Hull, R.A.: Cooperative control of dynamical systems with application to autonomous vehicles. Submitted to IEEE Transactions on Automatic Control
Qu, Z., Wang, J., Plaisted, C.E.: A New Analytical Solution to Mobile Robot Trajectory Generation in the Presence of Moving Obstacles. IEEE Transactions on Robotics 20, 978–993 (2004)
Guo, Y., Qu, Z.: Coverage control for a mobile robot patrolling a dynamic and uncertain environment. In: 5th World Congress on Intelligent Control and Automation, Hangzhou, China (Jan. 2004)
Reynolds, C.W.: Flocks, herds, and schools: a distributed behavioral model. Computer Graphics (ACM SIGGRAPH Conference Proceedings) 21, 25–34 (1987)
Vicsek, T., Czirok, A., Jacob, E.B., Cohen, I., Shochet, O.: Novel type of phase transition in a system of self-driven particles. Physical Review Letters 75, 1226–1229 (1995)
Jadbabaie, A., Lin, J., Morse, A.S.: Coordingation of groups of mobile autonomous agents using nearest neighbor rules. IEEE Trans. on Automatic Control 48, 988–1001 (2003)
Lin, Z., Brouchke, M., Francis, B.: Local control strategies for groups of mobile autonomous agents. IEEE Trans. on Automatic Control 49, 622–629 (2004)
Moreau, L.: Leaderless coordination via bidirectional and unidirectional time-dependent communication. In: Proceedings of the 42nd IEEE Conference on Decision and Control, Maui, Hawaii, IEEE, Los Alamitos (2003)
North Atlantic Treaty Organization: Standard Interfaces of the UAV Control System (UCS) for NATO UAV Interoperability (April 2004)
Dodson, C.: Jabber Technical White Paper, April 2000. Jabber.com, Inc. (2000)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yuan, H., Gottesman, V., Falash, M., Qu, Z., Pollak, E., Chunyu, J. (2007). Cooperative Formation Flying in Autonomous Unmanned Air Systems with Application to Training. In: Pardalos, P.M., Murphey, R., Grundel, D., Hirsch, M.J. (eds) Advances in Cooperative Control and Optimization. Lecture Notes in Control and Information Sciences, vol 369. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74356-9_13
Download citation
DOI: https://doi.org/10.1007/978-3-540-74356-9_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74354-5
Online ISBN: 978-3-540-74356-9
eBook Packages: EngineeringEngineering (R0)