Predictive monitoring research: Summary of the PREMON system

Traditional approaches to monitoring are proving inadequate in the face of two important issues: the dynamic adjustment of expectations about sensor values when the behavior of the device is too complex to enumerate beforehand, and the selective but effective interpretation of sensor readings when the number of sensors becomes overwhelming. This system addresses these issues by building an explicit model of a device and applying common-sense theories of physics to model causality in the device. The resulting causal simulation of the device supports planning decisions about how to efficiently yet reliably utilize a limited number of sensors to verify correct operation of the device

Information management in an integrated space telerobot

The in-orbit operations, like space structures inspection, servicing and repairing, is expected to be one of the most significant technological area for application and development of Robotics and Automation in Space Station environment. The Italian National Space Plan (PSN) has started up its strategic programme SPIDER (Space Inspection Device for Extravehicular Repairs), which is scheduled in three phases, with the final goal of performing docking and precision repairing in the Space Station environment. SPIDER system is an autonomous integrated space robot, using mature Artificial Intelligence tools and technics for its operational control. The preliminary results of a study on the information architecture of the spacecraft are described

A development framework for artificial intelligence based distributed operations support systems

Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself

The AI Bus architecture for distributed knowledge-based systems

The AI Bus architecture is layered, distributed object oriented framework developed to support the requirements of advanced technology programs for an order of magnitude improvement in software costs. The consequent need for highly autonomous computer systems, adaptable to new technology advances over a long lifespan, led to the design of an open architecture and toolbox for building large scale, robust, production quality systems. The AI Bus accommodates a mix of knowledge based and conventional components, running on heterogeneous, distributed real world and testbed environment. The concepts and design is described of the AI Bus architecture and its current implementation status as a Unix C++ library or reusable objects. Each high level semiautonomous agent process consists of a number of knowledge sources together with interagent communication mechanisms based on shared blackboards and message passing acquaintances. Standard interfaces and protocols are followed for combining and validating subsystems. Dynamic probes or demons provide an event driven means for providing active objects with shared access to resources, and each other, while not violating their security

A knowledge-based flight status monitor for real-time application in digital avionics systems

The Dryden Flight Research Facility of the National Aeronautics and Space Administration (NASA) Ames Research Center (Ames-Dryden) is the principal NASA facility for the flight testing and evaluation of new and complex avionics systems. To aid in the interpretation of system health and status data, a knowledge-based flight status monitor was designed. The monitor was designed to use fault indicators from the onboard system which are telemetered to the ground and processed by a rule-based model of the aircraft failure management system to give timely advice and recommendations in the mission control room. One of the important constraints on the flight status monitor is the need to operate in real time, and to pursue this aspect, a joint research activity between NASA Ames-Dryden and the Royal Aerospace Establishment (RAE) on real-time knowledge-based systems was established. Under this agreement, the original LISP knowledge base for the flight status monitor was reimplemented using the intelligent knowledge-based system toolkit, MUSE, which was developed under RAE sponsorship. Details of the flight status monitor and the MUSE implementation are presented

Plethora : a framework for the intelligent control of robotic assembly systems

Plethora : a framework for the intelligent control of robotic assembly system

Target Detection: New Techniques for Defence Applications

Discusses the machine interpretation of remotely-sensed in terms of human concepts by combining the techniques of artificial intelligence, pattern recognition and image analysis. Describes the solution to cognitive problem in registration, material classification, region extraction, structural analysis, semantic reasoning and problem solving architecture. The paper also discusses briefly the weapon-borne recognition systems using simulation and prediction models to hypothesise target appearance observed by sensors

Incremental planning to control a blackboard-based problem solver

To control problem solving activity, a planner must resolve uncertainty about which specific long-term goals (solutions) to pursue and about which sequences of actions will best achieve those goals. A planner is described that abstracts the problem solving state to recognize possible competing and compatible solutions and to roughly predict the importance and expense of developing these solutions. With this information, the planner plans sequences of problem solving activities that most efficiently resolve its uncertainty about which of the possible solutions to work toward. The planner only details actions for the near future because the results of these actions will influence how (and whether) a plan should be pursued. As problem solving proceeds, the planner adds new details to the plan incrementally, and monitors and repairs the plan to insure it achieves its goals whenever possible. Through experiments, researchers illustrate how these new mechanisms significantly improve problem solving decisions and reduce overall computation. They briefly discuss current research directions, including how these mechanisms can improve a problem solver's real-time response and can enhance cooperation in a distributed problem solving network

Knowledge-based processing for aircraft flight control

This Contractor Report documents research in Intelligent Control using knowledge-based processing in a manner dual to methods found in the classic stochastic decision, estimation, and control discipline. Such knowledge-based control has also been called Declarative, and Hybid. Software architectures were sought, employing the parallelism inherent in modern object-oriented modeling and programming. The viewpoint adopted was that Intelligent Control employs a class of domain-specific software architectures having features common over a broad variety of implementations, such as management of aircraft flight, power distribution, etc. As much attention was paid to software engineering issues as to artificial intelligence and control issues. This research considered that particular processing methods from the stochastic and knowledge-based worlds are duals, that is, similar in a broad context. They provide architectural design concepts which serve as bridges between the disparate disciplines of decision, estimation, control, and artificial intelligence. This research was applied to the control of a subsonic transport aircraft in the airport terminal area