Costing for the Future: Exploring Cost Estimation with Unmanned Autonomous Systems
AuthorRyan, Thomas Robert Jr.
Parametric Cost Estimation
Unmanned Autonomous Systems
Autonomous Cost Estimating Relationships
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PublisherThe University of Arizona.
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AbstractThis thesis explores three topics in the field of cost estimation for Unmanned Autonomous Systems. First, we propose a common definition of an Unmanned Autonomous System. We accomplish this through exhausting the literature in the areas cost estimation, autonomy in its current form, and how such advanced systems might be integrated into their environment. Second, we introduce a method to estimate the cost of Unmanned Autonomous Systems utilizing existing parametric cost estimation tools: SEER–HDR, COCOMO II, COSYSMO, and two cost estimating relationships–weight and performance. This discussion is guided by focusing on how current tools attempt to account for emergent systems. We also attempt to address challenges surrounding autonomy. To address these challenges from a cost perspective, this thesis recommends modifications to parameters within COCOMO II–via the use of object-oriented function points in lieu of current methods, and COSYSMO–via the introduction of two cost drivers namely, TVED and HRI-T. Third, we conduct analysis on four current Army Unmanned Autonomous Systems in an attempt to establish early trends within existing estimates. Finally, we explore areas of further research and discuss the implications of how pursing a more adequate cost model will lead to a better understanding of this ill-defined paradigm. *This material is based upon work supported by the Naval Postgraduate School Acquisition Research Program under Grant No. N00244-15-1-0008. The views expressed in written materials or publications, and/or made by speakers, moderators, and presenters, do not necessarily reflect the official policies of the Naval Postgraduate School nor does mention of trade names, commercial practices, or organizations imply endorsement by the U.S. Government.
Degree ProgramGraduate College