1 March 1992 Integrating control, simulation, and planning in MOSIM
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Abstract
Simulations have traditionally been used as off-line tools, for examining process models and experimenting with system models for which it would have been either impossible, too dangerous, expensive, or time-consuming to perform with the physical systems. We propose a novel way of regarding simulations as part of both the development and the working phases of systems. In our approach simulation is used within the processing and control loop of the system to provide sensor and state expectations. This minimizes the inverse sensory data analysis and model maintenance problems. We refer to this mode of operation as the verification mode, in contrast to the traditional discovery mode. This paper describes the integration of control, simulation, and planning within the mobile platform control and simulation interface program (MOSIM). MOSIM is a program which supports the combination of control and simulation of disparate platforms and environments. The main feature of MOSIM is the sensor simulations and the provision for capturing real sensory data and registering the simulated data with it. In order to provide simulations and planning that are intertwined with the control of a physical system, temporal issues have to be considered. By limiting the focus of the system to small portions of complex models which are temporarily relevant to the system's operation, the system is able to maintain its models and respond faster. For this we employ the context-based caching (CbC) mechanism within MOSIM. CbC is a novel knowledge management technique which maintains large knowledge bases by making the necessary information available at the right time.
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Yuval Roth-Tabak, Ramesh C. Jain, "Integrating control, simulation, and planning in MOSIM", Proc. SPIE 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics, (1 March 1992); doi: 10.1117/12.58580; https://doi.org/10.1117/12.58580
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KEYWORDS
Sensors

Computer simulations

Visualization

Data modeling

Systems modeling

Robotics

Artificial intelligence

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