Central Command Architecture for High-Order Autonomous Unmanned Aerial Systems

Abstract

This paper is the first in a two-part series that introduces an easy-to-implement central command architecture for high-order autonomous unmanned aerial systems. This paper discusses the development and the second paper presents the flight test results. As shown in this paper, the central command architecture consists of a central command block, an autonomous planning block, and an autonomous flight controls block. The central command block includes a staging process that converts an objective into tasks independent of the vehicle (agent). The autonomous planning block contains a non-iterative sequence of algorithms that govern routing, vehicle assignment, and deconfliction. The autonomous flight controls block employs modern controls principles, dividing the control input into a guidance part and a regulation part. A novel feature of high-order central command, as this paper shows, is the elimination of operator-directed vehicle tasking and the manner in which deconfliction is treated. A detailed example illustrates different features of the architecture.

Share and Cite:

Silverberg, L. and Bieber, C. (2014) Central Command Architecture for High-Order Autonomous Unmanned Aerial Systems. Intelligent Information Management, 6, 183-195. doi: 10.4236/iim.2014.64019.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Bellingham, J., Tillerson, M., Richards, A. and How, J.P. (2003) Multi-Task Allocation and Path Planning for Cooperative UAVs. In: Butenko, S., Murphey, R. and Pardalos, P.M., Eds., Cooperative Control: Models, Applications and Algorithms, Kluwer Academic Publishers, Boston, 23-39.
[2] Cummings, M.L., Bruni, S., Mercier, S. and Mitchell, P.J. (2007) Automation Architecture for Single Operator, Multiple UAV Command and Control. The International Command and Control Journal, 1, 1-24.
[3] Shima, T. and Rassmussen, S. (Eds.) (2009) UAV Cooperative Decision and Control. Society for Industrial and Applied Mathematics, Philadelphia.
http://dx.doi.org/10.1137/1.9780898718584
[4] Adams, J.A., Humphrey, C.M., Goodrich, M.A., Cooper, J.L., Morse, B.S., Engh, C. and Rasmussen, N. (2009) Cognitive Task Analysis for Developing Unmanned Aerial Vehicle Wilderness Search Support. Journal of Cognitive Engineering and Decision Making, 3, 1-26.
http://dx.doi.org/10.1518/155534309X431926
[5] Donmez, B.D., Nehme, C. and Cummings, M.L. (2010) Modeling Workload Impact in Multiple Unmanned Vehicle Supervisory Control. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 40, 1180-1190.
http://dx.doi.org/10.1109/TSMCA.2010.2046731
[6] Gardiner, B., Ahmad, W., Cooper, T., Haveard, M., Holt, J. and Biaz, S. (2011) Collision Avoidance Techniques for Unmanned Aerial Vehicles. Auburn University, Auburn.
[7] How, J., Ellis King, E. and Kuwata, Y. (2004) Flight Demonstrations of Cooperative Control for UAV Teams. AIAA 3rd “Unmanned Unlimited” Technical Conference, Workshop and Exhibit, Chicago, 20-23 September 2004.
[8] Edwards, D. and Silverberg, L.M. (2010) Autonomous Soaring: The Montague Cross-Country Challenge. Journal of Aircraft, 47, 1763-1769.
http://dx.doi.org/10.2514/1.C000287
[9] Levedahl, B. and Silverberg, L.M. (2005) Autonomous Coordination of Aircraft Formations Using Direct and Nearest-Neighbor Approaches. Journal of Aircraft, 42, 469-477.
http://dx.doi.org/10.2514/1.6868
[10] Tsourdos, A., White, B. and Shanmugavel, M. (2011) Cooperative Path Planning of Unmanned Aerial Vehicles. Wiley, New York.
[11] Lozano-Perez, T. and Wesley, M.A. (1979) An Algorithm for Planning Collision Free Paths among Polyhedral Obstacles. Communications of the ACM, 22, 560-570.
http://dx.doi.org/10.1145/359156.359164
[12] Hart, P.E., Nilsson, N.J. and Raphael, B. (1968) A Formal Basis for the Heuristic Determination of Minimum Cost Paths. IEEE Transactions on Systems Science and Cybernetics, 4, 100-107.
http://dx.doi.org/10.1109/TSSC.1968.300136
[13] Kuhn, H.W. (1955) The Hungarian Method for the Assignment Problem. Naval Research Logistics Quarterly, 2, 83-97.
[14] Dubins, L.E. (1957) On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents. American Journal of Mathematics, 79, 497-516.
http://dx.doi.org/10.2307/2372560
[15] Levedahl, B. and Silverberg, L.M. (2009) Control of Underwater Vehicles in Full Unsteady Flow. IEEE Journal of Oceanic Engineering, 34, 656-668.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.