摘要 :
As autonomous systems become more prevalent, it is crucial to develop new methods for ensuring their safety. The National Aeronautics and Space Administration (NASA)'s Robust Software Engineering (RSE) group is addressing this nee...
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As autonomous systems become more prevalent, it is crucial to develop new methods for ensuring their safety. The National Aeronautics and Space Administration (NASA)'s Robust Software Engineering (RSE) group is addressing this need with the development of the Research for Autonomous Vehicles (R-RAV) project, an autonomous rover testbed designed for assured autonomy research. In this paper, we describe how we used a Model-Based Systems Engineering (MBSE) approach to design and build the R-RAV and implemented our first autonomy research mission. The adoption of MBSE has allowed for efficient and data-driven collaboration, and has provided a comprehensive view of the system throughout its development, reducing ambiguity while increasing traceability and productivity. The R-RAV testbed will be used to advance research in assured autonomy, including safe machine learning, automated testing, and formal verification.
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摘要 :
As autonomous systems become more prevalent, it is crucial to develop new methods for ensuring their safety. The National Aeronautics and Space Administration (NASA)'s Robust Software Engineering (RSE) group is addressing this nee...
展开
As autonomous systems become more prevalent, it is crucial to develop new methods for ensuring their safety. The National Aeronautics and Space Administration (NASA)'s Robust Software Engineering (RSE) group is addressing this need with the development of the Research for Autonomous Vehicles (R-RAV) project, an autonomous rover testbed designed for assured autonomy research. In this paper, we describe how we used a Model-Based Systems Engineering (MBSE) approach to design and build the R-RAV and implemented our first autonomy research mission. The adoption of MBSE has allowed for efficient and data-driven collaboration, and has provided a comprehensive view of the system throughout its development, reducing ambiguity while increasing traceability and productivity. The R-RAV testbed will be used to advance research in assured autonomy, including safe machine learning, automated testing, and formal verification.
收起
摘要 :
As autonomous systems become more prevalent, it is crucial to develop new methods for ensuring their safety. The National Aeronautics and Space Administration (NASA)'s Robust Software Engineering (RSE) group is addressing this nee...
展开
As autonomous systems become more prevalent, it is crucial to develop new methods for ensuring their safety. The National Aeronautics and Space Administration (NASA)'s Robust Software Engineering (RSE) group is addressing this need with the development of the Research for Autonomous Vehicles (R-RAV) project, an autonomous rover testbed designed for assured autonomy research. In this paper, we describe how we used a Model-Based Systems Engineering (MBSE) approach to design and build the R-RAV and implemented our first autonomy research mission. The adoption of MBSE has allowed for efficient and data-driven collaboration, and has provided a comprehensive view of the system throughout its development, reducing ambiguity while increasing traceability and productivity. The R-RAV testbed will be used to advance research in assured autonomy, including safe machine learning, automated testing, and formal verification.
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