Engineering Papers⌕ Search

Engineering topics

Fisher, Forest

Publications and source records attributed to Fisher, Forest.

24 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Active State Model for Autonomous Systems

The concept of the active state model (ASM) is an architecture for the development of advanced integrated fault-detection-and-isolation (FDI) systems for robotic land vehicles, pilotless aircraft, exploratory spacecraft, or other complex engineering systems that will be capable of autonomous operation. An FDI system based on the ASM concept would not only provide traditional diagnostic capabilities, but also integrate the FDI system under a unified framework and provide mechanism for sharing of information between FDI subsystems to fully assess the overall health of the system. The ASM concept begins with definitions borrowed from psychology, wherein a system is regarded as active when it possesses self-image, self-awareness, and an ability to make decisions itself, such that it is able to perform purposeful motions and other transitions with some degree of autonomy from the environment. For an engineering system, self-image would manifest itself as the ability to determine nominal values of sensor data by use of a mathematical model of itself, and selfawareness would manifest itself as the ability to relate sensor data to their nominal values. The ASM for such a system may start with the closed-loop control dynamics that describe the evolution of state variables. As soon as this model was supplemented with nominal values of sensor data, it would possess self-image. The ability to process the current sensor data and compare them with the nominal values would represent self-awareness. On the basis of self-image and self-awareness, the ASM provides the capability for self-identification, detection of abnormalities, and self-diagnosis.

Park, Han↗
NASA NTRS2003

Rover traverse science for increased mission science return

In this paper, we will describe out methods for the prioritization of geologic data acquired by an in-situ rover. Our techniques are applicable to a wide range of data modalites, however out initial demonstration is focused on image analysis, as images consume a large volume of the downlink bandwidth for such missions.

data prioritization↗
NASA NTRS1999

Automated Planning for a Deep Space Communications Station

This paper describes the application of Artificial Intelligence planning techniques to the problem of antenna track plan generation for a NASA Deep Space Communications Station. Me described system enables an antenna communications station to automatically respond to a set of tracking goals by correctly configuring the appropriate hardware and software to provide the requested communication services. To perform this task, the Automated Scheduling and Planning Environment (ASPEN) has been applied to automatically produce antenna trucking plans that are tailored to support a set of input goals. In this paper, we describe the antenna automation problem, the ASPEN planning and scheduling system, how ASPEN is used to generate antenna track plans, the results of several technology demonstrations, and future work utilizing dynamic planning technology.

Estlin, Tara↗
NASA NTRS1998

An AI Approach to Ground Station Autonomy for Deep Space Communications

This paper describes an architecture for an autonomous deep space tracking station (DS-T). The architecture targets fully automated routine operations encompassing scheduling and resource allocation, antenna and receiver predict generation. track procedure generation from service requests, and closed loop control and error recovery for the station subsystems. This architecture has been validated by the construction of a prototype DS-T station, which has performed a series of demonstrations of autonomous ground station control for downlink services with NASA's Mars Global Surveyor (MGS).

Fisher, Forest↗