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Model-Based Simulation to Examine Command and Control Issues with Remotely Operated Vehicles

Model-Based Simulation to Examine Command and Control Issues with Remotely Operated Vehicles

Sasanka Prabhala, Subhashini Ganapathy, S. Narayanan, Jennie J. Gallimore, Raymond R. Hill
Copyright: © 2008 |Pages: 20
ISBN13: 9781599041988|ISBN10: 1599041987|ISBN13 Softcover: 9781616926861|EISBN13: 9781599042008
DOI: 10.4018/978-1-59904-198-8.ch007
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MLA

Prabhala, Sasanka, et al. "Model-Based Simulation to Examine Command and Control Issues with Remotely Operated Vehicles." Simulation and Modeling: Current Technologies and Applications, edited by Asim El Sheikh, et al., IGI Global, 2008, pp. 199-218. https://doi.org/10.4018/978-1-59904-198-8.ch007

APA

Prabhala, S., Ganapathy, S., Narayanan, S., Gallimore, J. J., & Hill, R. R. (2008). Model-Based Simulation to Examine Command and Control Issues with Remotely Operated Vehicles. In A. El Sheikh, A. Al Ajeeli, & E. Abu-Taieh (Eds.), Simulation and Modeling: Current Technologies and Applications (pp. 199-218). IGI Global. https://doi.org/10.4018/978-1-59904-198-8.ch007

Chicago

Prabhala, Sasanka, et al. "Model-Based Simulation to Examine Command and Control Issues with Remotely Operated Vehicles." In Simulation and Modeling: Current Technologies and Applications, edited by Asim El Sheikh, Abid Thyab Al Ajeeli, and Evon Abu-Taieh, 199-218. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-198-8.ch007

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Abstract

With increased interest in the overall employment of pilotless vehicles functioning in the ground, air, and marine domains for both defense and commercial applications, the need for high-fidelity simulation models for testing and validating the operational concepts associated with these systems is very high. This chapter presents a model-based approach that we adopted for investigating the critical issues in the command and control of remotely operated vehicles (ROVs) through an interactive model-based architecture. The domain of ROVs is highly dynamic and complex in nature. Hence, a proper understanding of the simulation tools, underlying system algorithms, and user needs is critical to realize advanced simulation system concepts. Our resulting simulation architecture integrates proven design concepts such as the model-view-controller paradigm, distributed computing, Web-based simulations, cognitive model-based high-fidelity interfaces and object-based modeling methods.

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