Abstract
In this study, our focus is on the design of mission scheduling techniques capable of working in dynamic environments with unmanned aerial vehicles, to determine effective mission schedules in real time. The effectiveness of mission schedules for unmanned aerial vehicles is measured using a surveillance value metric, which incorporates information about the amount and usefulness of information obtained from surveilling targets. We design a set of dynamic heuristic techniques, which are compared and evaluated based on their ability to maximize surveillance value in a wide range of scenarios generated by a randomized model. We consider two comparison heuristics, three value-based heuristics, and a metaheuristic that intelligently switches between the best value-based heuristics. The novel metaheuristic is shown to find effective solutions that are the best on average as all other techniques that we evaluate in all scenarios that we consider.
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
References
J. Crowder, J. Carbone, Autonomous mission planner and supervisor (AMPS) for UAVs, in 20th International Conference on Artificial Intelligence (ICAI ‘18), (July 2018), pp. 195–201
M.R. Garey, D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness (W. H. Freeman and Co, 1979)
R.D. Friese, J.A. Crowder, H.J. Siegel, J.N. Carbone, Bi-objective study for the assignment of unmanned aerial vehicles to targets, in 20th International Conference on Artificial Intelligence (ICAI ‘18), (July 2018), pp. 207–213
R.D. Friese, J.A. Crowder, H.J. Siegel, J.N. Carbone, Surveillance mission planning: Model, performance measure, bi-objective analysis, partial surveils, in 21st International Conference on Artificial Intelligence (ICAI ‘19), (July 2019), 7 pp
D. Machovec, B. Khemka, N. Kumbhare, S. Pasricha, A.A. Maciejewski, H.J. Siegel, A. Akoglu, G.A. Koenig, S. Hariri, C. Tunc, M. Wright, M. Hilton, R. Rambharos, C. Blandin, F. Fargo, A. Louri, N. Imam, Utility-based resource management in an oversubscribed energy-constrained heterogeneous environment executing parallel applications. Parallel Comput. 83, 48–72 (2019)
B. Khemka, R. Friese, S. Pasricha, A.A. Maciejewski, H.J. Siegel, G.A. Koenig, S. Powers, M. Hilton, R. Rambharos, S. Poole, Utility maximizing dynamic resource management in an oversubscribed energy-constrained heterogeneous computing system. Sustain. Comput. Inform. Syst. 5, 14–30 (2015)
J.J. Wang, Y.F. Zhang, L. Geng, J.Y.H. Fuh, S.H. Teo, Mission planning for heterogeneous tasks with heterogeneous UAVs, in 13th International Conference on Control Automation Robotics & Vision (ICARCV), (March 2014), pp. 1484–1489
C. Schumacher, P. Chandler, M. Pachter, L. Pachter, UAV task assignment with timing constraints, in AIAA Guidance, Navigation, and Control Conference and Exhibit, (June 2003), 9 pp
J. Zeng, X. Yang, L. Yang, G. Shen, Modeling for UAV resource scheduling under mission synchronization. J. Syst. Eng. Electron. 21(5), 821–826 (2010)
S. Leary, M. Deittert, J. Bookless, Constrained UAV mission planning: A comparison of approaches, in 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2002–2009, (November 2011)
L. Evers, T. Dollevoet, A.I. Barros, H. Monsuur, Robust UAV mission planning. Ann. Oper. Res. 222, 293–315 (2012)
F. Mufalli, R. Batta, R. Nagi, Simultaneous sensor selection and routing of unmanned aerial vehicles for complex mission plans. Comput. Oper. Res. 39, 2787–2799 (2012)
W. Chung, V. Crespi, G. Cybenko, A. Jordan, Distributed sensing and UAV scheduling for surveillance and tracking of unidentifiable targets, in Proceedings of SPIE 5778, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IV, (May 2005), pp. 226–235
D. Pascarella, S. Venticinque, R. Aversa, Agent-based design for UAV mission planning, in 8th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), (October 2013), pp. 76–83
J. Kim, B.D. Song, J.R. Morrison, On the scheduling of systems of UAVs and fuel service stations for long-term mission fulfillment. J. Intell. Robot. Syst. 70, 347–359 (2013)
W. Yang, L. Lei, J. Deng, Optimization and improvement for multi-UAV cooperative reconnaissance mission planning problem, in 11th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), (December 2014), pp. 10–15
M. Faied, A. Mostafa, A. Girard, Vehicle routing problem instances: Application to multi-UAV mission planning, in AIAA Guidance, Navigation, and Control Conference, (August 2010), 12 pp
G.Q. Li, X.G. Zhou, J. Yin, Q.Y. Xiao, An UAV scheduling and planning method for post-disaster survey. ISPRS – Int. Arch. Photogramm. Remote. Sens. Spat. Inf. Sci. XL-2, 169–172 (2014)
Acknowledgments
The authors thank Ryan D. Friese and John N. Carbone for their comments on this research.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Machovec, D., Crowder, J.A., Siegel, H.J., Pasricha, S., Maciejewski, A.A. (2021). Dynamic Heuristics for Surveillance Mission Scheduling with Unmanned Aerial Vehicles in Heterogeneous Environments. In: Arabnia, H.R., Ferens, K., de la Fuente, D., Kozerenko, E.B., Olivas Varela, J.A., Tinetti, F.G. (eds) Advances in Artificial Intelligence and Applied Cognitive Computing. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-70296-0_43
Download citation
DOI: https://doi.org/10.1007/978-3-030-70296-0_43
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-70295-3
Online ISBN: 978-3-030-70296-0
eBook Packages: Computer ScienceComputer Science (R0)