The Design of Real-Time Expert Systems for Autonomous Vehicles

这项建议是为了研究用于自主水下机器人(AUV)系统的基于知识的系统设计中的关键问题的研究计划。它定义了一种努力，以了解与在实时系统中利用基于知识的系统相关的一些问题。这项研究的目的是实现一个框架，以进一步开发基于实时知识的系统。这一框架将通过开发适用于时间受限符号系统的操作系统和系统架构来实现。这项工作的主要成果将是一种新的符号处理操作系统，它将被用作智能时间受限系统当前和未来发展的基础。拟议的研究解决了导致有能力的实时系统的潜在问题。基于知识的技术将通过首先从操作系统和系统体系结构的优势来解决设计问题来推进。拟议的工作将利用当前的实时操作系统技术。一旦选择了体系结构和应用程序，它将在驻留在Ironics IV 3204 32位CPU板上的MSEL集成符号数字系统上实现。测试阶段将包括确定和测量关键实时系统参数以及基准。在这一点上，除了简单的周期费率确定之外，没有明确的业绩衡量标准。为此，提出了一项任务，以确定用于评估时间受限的基于知识的系统的有用指标。在这项工作的最后阶段，我们将对结果进行评估，以确定性能限制并对系统提出改进建议。

This proposal is for a research program that investigates key issues in the design of knowledge based systems for use in Autonomous Undersea Vehicle (AUV) systems. It defines an effort to understand some of the problems associated with utilizing knowledge based systems in real time systems. The purpose of this research is to implement a framework for further development of real time knowledge based systems. this framework will be realized with the development of an operating system and system architecture applicable to time constrained symbolic systems. The main product of this effort will be a new symbolic processing operating system which will be used as the foundation for current and future development in intelligent time constrained systems. The proposed research addressed the underlying issues which lead to capable real time systems. Knowledge based techniques will be advanced by first addressing the design from the vantage of operating systems and system architecture. The proposed work will take advantage of current real time operating system technology. Once the architecture a and application is chosen it will be implemented on the MSEL integrated symbolic numeric system residing on the Ironics IV 3204 32 bit CPU board for VME bus. The testing phase will include the determination and measurement of key real time system parameters as well as benchmarks. At this point there are no clear measures of performance other than simplistic cycle rate determinations. For this reason a task is included to determine useful metrics for evaluating time constrained knowledge-based systems. In the final phase of this work we will evaluate the results to determine performance limitations and propose enhancements to the system.