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Int. J. Operational Research, Vol. 7, No. 2, 2010
A multiple criteria decision support system for autonomous underwater vehicle mission planning and control Madjid Tavana* Management Information Systems, Lindback Distinguished Chair of Information Systems, La Salle University, Philadelphia, PA 19141, USA E-mail:
[email protected] Website: http://lasalle.edu/~tavana *Corresponding author
Brian S. Bourgeois Naval Research Laboratory, Marine Geosciences Division, Stennis Space Center, MS 39529, USA E-mail:
[email protected] Abstract: The growing use of autonomous air, surface, ground and underwater systems is continually demonstrating new military and commercial possibilities and applications. The state of the art in the planning and control of autonomous underwater vehicles (AUVs) is largely precarious because AUVs provide infrequent feedback, operate autonomously for long periods of time and yet have little knowledge of their dynamic environment. Consequently, mission planning and control is typically conducted based on human expert knowledge of vehicle capabilities, some level of observed environmental conditions and ad hoc optimisation with little assistance from computers. While the human expert offers a significant ability to mentally process data, the result typically lacks numeric and quantitative analysis of alternatives. Navigation of AUVs in the complex ocean environment involves time dependent dynamics, resulting in a problem that is computationally prohibitive for the use of brute force optimisation techniques. Although some research has been conducted for specific types of missions, and ‘greedy’ global-optimisation approaches have been investigated, no systematic and coherent approach to the requirement exists. We propose a dynamic multiple criteria decision support system that considers dynamic and episodic ocean phenomenon to provide reasonable and in-context recommendations with respect to the stated objective and subjective mission goals. Multi-criteria decision analysis, analytic network process and fuzzy sets are used in the model to reduce the vehicle routing solution space and maximise time-on station in adverse environments. The proposed system can be an added hierarchical layer on the top of a mission planning system currently under development by the United States Navy. Keywords: ANP; analytic network process; AUV; autonomous underwater vehicles; DSS; decision support systems; fuzzy sets; geographical information system; mission planning and control; MCDA; multi-criteria decision analysis; vehicle routing.
Copyright © 2010 Inderscience Enterprises Ltd.
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Reference to this paper should be made as follows: Tavana, M. and Bourgeois, B.S. (2010) ‘A multiple criteria decision support system for autonomous underwater vehicle mission planning and control’, Int. J. Operational Research, Vol. 7, No. 2, pp.216–239. Biographical notes: Madjid Tavana is a Professor of Management Information Systems and the Lindback Distinguished Chair of Information Systems at the La Salle University, where he served as the Chairman of the Management Department and Director of the Center for Technology and Management. He has been a Distinguished Faculty Fellow at the NASA’s Kennedy Space Center, NASA’s Johnson Space Center, Naval Research Laboratory – Stennis Space Center and Air Force Research Laboratory. In 2005, he was awarded the prestigious Space Act Award by NASA. He holds an MBA, a PMIS and a PhD in Management Information Systems. He received his PostDoctoral Diploma in Strategic Information Systems from the Wharton School of the University of Pennsylvania. He has published in journals such as Decision Sciences, Interfaces, Information Systems, Information and Management, Computers and Operations Research, Journal of the Operational Research Society and Advances in Engineering Software, among others. Brian Bourgeois is a Section Head in the Geosciences Division of the Naval Research Laboratory (NRL) at the Stennis Space Center. He holds a PhD in Electrical Engineering from Tulane University. His areas of research have spanned bathymetry sonar systems, unmanned underwater vehicles, underwater navigation systems, automated vehicle navigation and most recently GIS-based mission planning systems. He has received three NRL technology transition awards and the Berman publication award, has five patents and has published over 50 journal and conference papers. He is a senior member of IEEE and is on the editorial board of the Int. J. Strategic Decision Sciences and Int. J. Applied Decision Sciences. Disclaimer: The views expressed in this article are those of the authors and do not reflect the official policy or position of the United States Department of Defense.
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Introduction
We know more about the moon than we do about our own planet and the environment that covers over two-thirds of its surface. Observing the ocean is a challenging endeavour, made difficult by a wide range of time and environmental conditions and constraints. In recent years, autonomous underwater vehicles (AUVs) are being used to help conquer that challenge (Roemmich et al., 2004; Rudnick et al., 2004). The growing use of autonomous air, surface, ground and underwater systems is continually demonstrating new military and commercial possibilities and applications. Underwater vehicles are used primarily by scientists as oceanographic tools to navigate autonomously and map features of the ocean. Government forces use AUVs for global war on terrorism. The United States Navy uses underwater vehicles to safely gain access to denied areas with revolutionary sensors and weapons for mine warfare; intelligence, surveillance, and reconnaissance; undersea environmental sensing and mapping. The oil and gas industry uses AUVs to make detailed maps of the seafloor before building subsea infrastructure. These detailed maps allow cost effective installation of
