NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

A methodology to produce geographical information for land planning using very-high resolution images

Actualmente, os municípios são obrigados a produzir, no âmbito da elaboração dos instrumentos de gestão territorial, cartografia homologada pela autoridade nacional. O Plano Director Municipal (PDM) tem um período de vigência de 10 anos. Porém, no que diz respeito à cartografia para estes planos, principalmente em municípios onde a pressão urbanística é elevada, esta periodicidade não é compatível com a dinâmica de alteração de uso do solo. Emerge assim, a necessidade de um processo de produção mais eficaz, que permita a obtenção de uma nova cartografia de base e temática mais frequentemente. Em Portugal recorre-se à fotografia aérea como informação de base para a produção de cartografia de grande escala. Por um lado, embora este suporte de informação resulte em mapas bastante rigorosos e detalhados, a sua produção têm custos muito elevados e consomem muito tempo. As imagens de satélite de muito alta-resolução espacial podem constituir uma alternativa, mas sem substituir as fotografias aéreas na produção de cartografia temática, a grande escala. O tema da tese trata assim da satisfação das necessidades municipais em informação geográfica actualizada. Para melhor conhecer o valor e utilidade desta informação, realizou-se um inquérito aos municípios Portugueses. Este passo foi essencial para avaliar a pertinência e a utilidade da introdução de imagens de satélite de muito alta-resolução espacial na cadeia de procedimentos de actualização de alguns temas, quer na cartografia de base quer na cartografia temática. A abordagem proposta para solução do problema identificado baseia-se no uso de imagens de satélite e outros dados digitais em ambiente de Sistemas de Informação Geográfica. A experimentação teve como objectivo a extracção automática de elementos de interesse municipal a partir de imagens de muito alta-resolução espacial (fotografias aéreas ortorectificadas, imagem QuickBird, e imagem IKONOS), bem como de dados altimétricos (dados LiDAR). Avaliaram-se as potencialidades da informação geográfica extraídas das imagens para fins cartográficos e analíticos. Desenvolveram-se quatro casos de estudo que reflectem diferentes usos para os dados geográficos a nível municipal, e que traduzem aplicações com exigências diferentes. No primeiro caso de estudo, propõe-se uma metodologia para actualização periódica de cartografia a grande escala, que faz uso de fotografias aéreas vi ortorectificadas na área da Alta de Lisboa. Esta é uma aplicação quantitativa onde as qualidades posicionais e geométricas dos elementos extraídos são mais exigentes. No segundo caso de estudo, criou-se um sistema de alarme para áreas potencialmente alteradas, com recurso a uma imagem QuickBird e dados LiDAR, no Bairro da Madre de Deus, com objectivo de auxiliar a actualização de cartografia de grande escala. No terceiro caso de estudo avaliou-se o potencial solar de topos de edifícios nas Avenidas Novas, com recurso a dados LiDAR. No quarto caso de estudo, propõe-se uma série de indicadores municipais de monitorização territorial, obtidos pelo processamento de uma imagem IKONOS que cobre toda a área do concelho de Lisboa. Esta é uma aplicação com fins analíticos onde a qualidade temática da extracção é mais relevante.Currently, the Portuguese municipalities are required to produce homologated cartography, under the Territorial Management Instruments framework. The Municipal Master Plan (PDM) has to be revised every 10 years, as well as the topographic and thematic maps that describe the municipal territory. However, this period is inadequate for representing counties where urban pressure is high, and where the changes in the land use are very dynamic. Consequently, emerges the need for a more efficient mapping process, allowing obtaining recent geographic information more often. Several countries, including Portugal, continue to use aerial photography for large-scale mapping. Although this data enables highly accurate maps, its acquisition and visual interpretation are very costly and time consuming. Very-High Resolution (VHR) satellite imagery can be an alternative data source, without replacing the aerial images, for producing large-scale thematic cartography. The focus of the thesis is the demand for updated geographic information in the land planning process. To better understand the value and usefulness of this information, a survey of all Portuguese municipalities was carried out. This step was essential for assessing the relevance and usefulness of the introduction of VHR satellite imagery in the chain of procedures for updating land information. The proposed methodology is based on the use of VHR satellite imagery, and other digital data, in a Geographic Information Systems (GIS) environment. Different algorithms for feature extraction that take into account the variation in texture, color and shape of objects in the image, were tested. The trials aimed for automatic extraction of features of municipal interest, based on aerial and satellite high-resolution (orthophotos, QuickBird and IKONOS imagery) as well as elevation data (altimetric information and LiDAR data). To evaluate the potential of geographic information extracted from VHR images, two areas of application were identified: mapping and analytical purposes. Four case studies that reflect different uses of geographic data at the municipal level, with different accuracy requirements, were considered. The first case study presents a methodology for periodic updating of large-scale maps based on orthophotos, in the area of Alta de Lisboa. This is a situation where the positional and geometric accuracy of the extracted information are more demanding, since technical mapping standards must be complied. In the second case study, an alarm system that indicates the location of potential changes in building areas, using a QuickBird image and LiDAR data, was developed for the area of Bairro da Madre de Deus. The goal of the system is to assist the updating of large scale mapping, providing a layer that can be used by the municipal technicians as the basis for manual editing. In the third case study, the analysis of the most suitable roof-tops for installing solar systems, using LiDAR data, was performed in the area of Avenidas Novas. A set of urban environment indicators obtained from VHR imagery is presented. The concept is demonstrated for the entire city of Lisbon, through IKONOS imagery processing. In this analytical application, the positional quality issue of extraction is less relevant.GEOSAT – Methodologies to extract large scale GEOgraphical information from very high resolution SATellite images (PTDC/GEO/64826/2006), e-GEO – Centro de Estudos de Geografia e Planeamento Regional, da Faculdade de Ciências Sociais e Humanas, no quadro do Grupo de Investigação Modelação Geográfica, Cidades e Ordenamento do Territóri

The Sixth Annual Workshop on Space Operations Applications and Research (SOAR 1992)

This document contains papers presented at the Space Operations, Applications, and Research Symposium (SOAR) hosted by the U.S. Air Force (USAF) on 4-6 Aug. 1992 and held at the JSC Gilruth Recreation Center. The symposium was cosponsored by the Air Force Material Command and by NASA/JSC. Key technical areas covered during the symposium were robotic and telepresence, automation and intelligent systems, human factors, life sciences, and space maintenance and servicing. The SOAR differed from most other conferences in that it was concerned with Government-sponsored research and development relevant to aerospace operations. The symposium's proceedings include papers covering various disciplines presented by experts from NASA, the USAF, universities, and industry

NASA/NBS (National Aeronautics and Space Administration/National Bureau of Standards) standard reference model for telerobot control system architecture (NASREM)

The document describes the NASA Standard Reference Model (NASREM) Architecture for the Space Station Telerobot Control System. It defines the functional requirements and high level specifications of the control system for the NASA space Station document for the functional specification, and a guideline for the development of the control system architecture, of the 10C Flight Telerobot Servicer. The NASREM telerobot control system architecture defines a set of standard modules and interfaces which facilitates software design, development, validation, and test, and make possible the integration of telerobotics software from a wide variety of sources. Standard interfaces also provide the software hooks necessary to incrementally upgrade future Flight Telerobot Systems as new capabilities develop in computer science, robotics, and autonomous system control

Performance Analysis of Live-Virtual-Constructive and Distributed Virtual Simulations: Defining Requirements in Terms of Temporal Consistency

This research extends the knowledge of live-virtual-constructive (LVC) and distributed virtual simulations (DVS) through a detailed analysis and characterization of their underlying computing architecture. LVCs are characterized as a set of asynchronous simulation applications each serving as both producers and consumers of shared state data. In terms of data aging characteristics, LVCs are found to be first-order linear systems. System performance is quantified via two opposing factors; the consistency of the distributed state space, and the response time or interaction quality of the autonomous simulation applications. A framework is developed that defines temporal data consistency requirements such that the objectives of the simulation are satisfied. Additionally, to develop simulations that reliably execute in real-time and accurately model hierarchical systems, two real-time design patterns are developed: a tailored version of the model-view-controller architecture pattern along with a companion Component pattern. Together they provide a basis for hierarchical simulation models, graphical displays, and network I/O in a real-time environment. For both LVCs and DVSs the relationship between consistency and interactivity is established by mapping threads created by a simulation application to factors that control both interactivity and shared state consistency throughout a distributed environment

The 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies

This publication comprises the papers presented at the 1995 Goddard Conference on Space Applications of Artificial Intelligence and Emerging Information Technologies held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland, on May 9-11, 1995. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed

Center for Advanced Space Propulsion Second Annual Technical Symposium Proceedings

The proceedings for the Center for Advanced Space Propulsion Second Annual Technical Symposium are divided as follows: Chemical Propulsion, CFD; Space Propulsion; Electric Propulsion; Artificial Intelligence; Low-G Fluid Management; and Rocket Engine Materials

Fourth Conference on Artificial Intelligence for Space Applications

Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming

LiDAR-based Semantic Labeling : Automotive 3D Scene Understanding

Mobile Roboter und autonome Fahrzeuge verwenden verschiedene Sensormodalitäten zur Erkennung und Interpretation ihrer Umgebung. Neben Kameras und RaDAR Sensoren repräsentieren LiDAR Sensoren eine zentrale Komponente für moderne Methoden der Umgebungswahrnehmung. Zusätzlich zu einer präzisen Distanzmessung dieser Sensoren, ist ein umfangreiches semantisches Szeneverständnis notwendig, um ein effizientes und sicheres Agieren autonomer Systeme zu ermöglichen. In dieser Arbeit wird das neu entwickelte LiLaNet, eine echtzeitfähige, neuronale Netzarchitektur zur semantischen, punktweisen Klassifikation von LiDAR Punktwolken, vorgestellt. Hierfür finden die Ansätze der 2D Bildverarbeitung Verwendung, indem die 3D LiDAR Punktwolke als 2D zylindrisches Bild dargestellt wird. Dadurch werden Ergebnisse moderner Ansätze zur LiDAR-basierten, punktweisen Klassifikation übertroffen, was an unterschiedlichen Datensätzen demonstriert wird. Zur Entwicklung von Ansätzen des maschinellen Lernens, wie sie in dieser Arbeit verwendet werden, spielen umfangreiche Datensätze eine elementare Rolle. Aus diesem Grund werden zwei Datensätze auf Basis von modernen LiDAR Sensoren erzeugt. Durch das in dieser Arbeit entwickelte automatische Verfahren zur Datensatzgenerierung auf Basis von mehreren Sensormodalitäten, speziell der Kamera und des LiDAR Sensors, werden Kosten und Zeit der typischerweise manuellen Datensatzgenerierung reduziert. Zusätzlich wird eine multimodale Datenkompression vorgestellt, welche ein Kompressionsverfahren der Stereokamera auf den LiDAR Sensor überträgt. Dies führt zu einer Reduktion der LiDAR Daten bei gleichzeitigem Erhalt der zugrundeliegenden semantischen und geometrischen Information. Daraus resultiert eine erhöhte Echtzeitfähigkeit nachgelagerter Algorithmen autonomer Systeme. Außerdem werden zwei Erweiterungen zum vorgestellten Verfahren der semantischen Klassifikation umrissen. Zum einen wird die Sensorabhängigkeit durch Einführung des PiLaNets, einer neuen 3D Netzarchitektur, reduziert indem die LiDAR Punktwolke im 3D kartesischen Raum belassen wird, um die eher sensorabhängige 2D zylindrische Projektion zu ersetzen. Zum anderen wird die Unsicherheit neuronaler Netze implizit modelliert, indem eine Klassenhierarchie in den Trainingsprozess integriert wird. Insgesamt stellt diese Arbeit neuartige, performante Ansätze des 3D LiDAR-basierten, semantischen Szeneverstehens vor, welche zu einer Verbesserung der Leistung, Zuverlässigkeit und Sicherheit zukünftiger mobile Roboter und autonomer Fahrzeuge beitragen