Information Technology & Software

Planning Complex Sequences Using Compressed Representations

Computation time and memory needed to generate schedules are greatly reduced.

A method that notably includes the use of compressed representations interleaved with non-compressed (time-line) representations of a general scheduling problem has been conceived as a means of increasing, by orders of magnitude, the speeds of computations needed for scheduling complex sequences of activities that include cycles wherein subsets of the activities and/or sequences are repeated. The method was originally intended to be used in scheduling large campaigns of scientific observations by instruments aboard a spacecraft. A typical such campaign could include observations of millions of targets, many observations to be made during long repeated passes. The method would also be useful on Earth for scheduling complex sequences of activities that include cycles.

The method is best summarized in the context of the original intended application, wherein the scheduling problem is formulated as that of selecting, from a candidate set of observations, those observations that cover as many target points as possible without oversubscribing energy and memory budgets. Inasmuch as observation opportunities repeat, the theoretical framework for evaluation of candidate solutions includes a cycle bound.

Posted in: Briefs, Information Sciences, Mathematical models, Logistics, Test procedures
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Self-Supervised Learning of Terrain Traversability From Proprioceptive Sensors

This system enables a vehicle to scan its surroundings and adapt to conditions by learning about them on the fly.

Robust and reliable autonomous navigation in unstructured, off-road terrain is a critical element in making unmanned ground vehicles a reality. Existing approaches tend to rely on evaluating the traversability of terrain based on fixed parameters obtained via testing in specific environments. This results in a system that handles the terrain well that it trained in, but is unable to process terrain outside its test parameters.

Posted in: Briefs, Information Sciences, Artificial intelligence, Sensors and actuators, Artificial intelligence, Sensors and actuators, Terrain, Autonomous vehicles
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A Software Rejuvenation Framework for Distributed Computing

This framework supports graceful degradation of services at best possible performance levels.

A performability-oriented conceptual framework for software rejuvenation has been constructed as a means of increasing levels of reliability and performance in distributed stateful computing. As used here, “performability-oriented” signifies that the construction of the framework is guided by the concept of analyzing the ability of a given computing system to deliver services with gracefully degradable performance. The framework is especially intended to support applications that involve stateful replicas of server computers.

Posted in: Briefs, Information Sciences, Mathematical models, Architecture, Computer software / hardware, Computer software and hardware, Architecture, Computer software / hardware, Computer software and hardware, Performance upgrades
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Kurtosis Approach to Solution of a Nonlinear ICA Problem

A gradient-descent algorithm minimizes the kurtosis of an output vector.

An algorithm for solving a particular nonlinear independent-component-analysis (ICA) problem, that differs from prior algorithms for solving the same problem, has been devised. The problem in question — of a type known in the art as a post nonlinear mixing problem — is a useful approximation of the problem posed by the mixing and subsequent nonlinear distortion of sensory signals that occur in diverse scientific and engineering instrumentation systems.

Posted in: Briefs, Information Sciences
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Robust Software Architecture for Robots

Generalized software can be readily tailored for specific applications.

“Robust Real-Time Reconfigurable Robotics Software Architecture” (“R4SA”) is the name of both a software architecture and software that embodies the architecture. The architecture was conceived in the spirit of current practice in designing modular, hard, real-time aerospace systems. The architecture facilitates the integration of new sensory, motor, and control software modules into the software of a given robotic system. R4SA was developed for initial application aboard exploratory mobile robots on Mars, but is adaptable to terrestrial robotic systems, real-time embedded computing systems in general, and robotic toys.

Posted in: Briefs, TSP, Information Sciences, Adaptive control, Architecture, Computer software / hardware, Computer software and hardware, Adaptive control, Architecture, Computer software / hardware, Computer software and hardware, Robotics
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R4SA for Controlling Robots

The R4SA GUI mentioned in the immediately preceding article is a user-friendly interface for controlling one or more robot(s). This GUI makes it possible to perform meaningful real-time field experiments and research in robotics at an unmatched level of fidelity, within minutes of setup. It provides such powerful graphing modes as that of a digitizing oscilloscope that displays up to 250 variables at rates between 1 and 200 Hz. This GUI can be configured as multiple intuitive interfaces for acquisition of data, command, and control to enable rapid testing of subsystems or an entire robot system while simultaneously performing analysis of data.

Posted in: Briefs, TSP, Information Sciences, Human machine interface (HMI), Robotics
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Bio-Inspired Neural Model for Learning Dynamic Models

This model could be a basis for fast speech- and image-recognition computers.

A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be “hardware-friendly” in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.

Posted in: Briefs, Information Sciences
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Evolutionary Computing Methods for Spectral Retrieval

Solutions to the inverse problem of spectral retrieval are found in a computationally efficient process.

A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest.

Posted in: Briefs, TSP, Information Sciences
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Monitoring Disasters by Use of Instrumented Robotic Aircraft

Real-time synoptic data would help in coordinating and planning responses.

Efforts are under way to develop data- acquisition, data- processing, and data- communication systems for monitoring disasters over large geographic areas by use of uninhabited aerial systems (UAS) — robotic aircraft that are typically piloted by remote control. As integral parts of advanced, comprehensive disaster-management programs, these systems would provide (1) real-time data that would be used to coordinate responses to current disasters and (2) recorded data that would be used to model disasters for the purpose of mitigating the effects of future disasters and planning responses to them.

Posted in: Briefs, Information Sciences, Disaster and emergency management, Emergency management, Robotics, Hazards and emergency management, Hazards and emergency operations, Unmanned aerial vehicles
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Complexity for Survival of Living Systems

Interactions between systems and their mental images enable unlimited increase of complexity.

A logical connection between the survivability of living systems and the complexity of their behavior (equivalently, mental complexity) has been established. This connection is an important intermediate result of continuing research on mathematical models that could constitute a unified representation of the evolution of both living and non-living systems. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the two most relevant being “Characteristics of Dynamics of Intelligent Systems” (NPO- 21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; and “Self-Supervised Dynamical Systems” (NPO- 30634) NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72.

Posted in: Briefs, Information Sciences, Mathematical models, Biological sciences
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