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NASA NTRS2014

UAS Conflict-Avoidance Using Multiagent RL with Abstract Strategy Type Communication

The use of unmanned aerial systems (UAS) in the national airspace is of growing interest to the research community. Safety and scalability of control algorithms are key to the successful integration of autonomous system into a human-populated airspace. In order to ensure safety while still maintaining efficient paths of travel, these algorithms must also accommodate heterogeneity of path strategies of its neighbors. We show that, using multiagent RL, we can improve the speed with which conflicts are resolved in cases with up to 80 aircraft within a section of the airspace. In addition, we show that the introduction of abstract agent strategy types to partition the state space is helpful in resolving conflicts, particularly in high congestion.

Unmanned Autonomous Systems↗

NASA NTRS2014

Announced Strategy Types in Multiagent RL for Conflict-Avoidance in the National Airspace

National Airspace↗

NASA NTRS2005

Intelligent Vehicle Health Management

As a part of the overall goal of developing Integrated Vehicle Health Management systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of INM. These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the INM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project and the integration of these technologies forms the framework for IIVM.

Paris, Deidre E.↗

NASA NTRS2012

Use of the Earth Observing One (EO-1) Satellite for the Namibia SensorWeb Flood Early Warning Pilot

The Earth Observing One (EO-1) satellite was launched in November 2000 as a one year technology demonstration mission for a variety of space technologies. After the first year, it was used as a pathfinder for the creation of SensorWebs. A SensorWeb is the integration of variety of space, airborne and ground sensors into a loosely coupled collaborative sensor system that automatically provides useful data products. Typically, a SensorWeb is comprised of heterogeneous sensors tied together with a messaging architecture and web services. Disasters are the perfect arena to use SensorWebs. One SensorWeb pilot project that has been active since 2009 is the Namibia Early Flood Warning SensorWeb pilot project. The Pilot Project was established under the auspices of the Namibian Ministry of Agriculture Water and Forestry (MAWF)/Department of Water Affairs, the Committee on Earth Observing Satellites (CEOS)/Working Group on Information Systems and Services (WGISS) and moderated by the United Nations Platform for Space-based Information for Disaster Management and Emergency Response (UN-SPIDER). The effort began by identifying and prototyping technologies which enabled the rapid gathering and dissemination of both space-based and ground sensor data and data products for the purpose of flood disaster management and water-borne disease management. This was followed by an international collaboration to build small portions of the identified system which was prototyped during that past few years during the flood seasons which occurred in the February through May timeframe of 2010 and 2011 with further prototyping to occur in 2012. The SensorWeb system features EO-1 data along with other data sets from such satellites as Radarsat, Terra and Aqua. Finally, the SensorWeb team also began to examine the socioeconomic component to determine the impact of the SensorWeb technology and how best to assist in the infusion of this technology in lesser affluent areas with low levels of basic infrastructure. This paper provides an overview of these efforts, highlighting the EO-1 usage in this SensorWeb.

Mandl, Daniel↗

NASA NTRS2012

SensorWeb Evolution Using the Earth Observing One (EO-1) Satellite as a Test Platform

The Earth Observing One (EO-1) satellite was launched in November 2000 as a one year technology demonstration mission for a variety of space technologies. After the first year, in addition to collecting science data from its instruments, the EO-1 mission has been used as a testbed for a variety of technologies which provide various automation capabilities and which have been used as a pathfinder for the creation of SensorWebs. A SensorWeb is the integration of variety of space, airborne and ground sensors into a loosely coupled collaborative sensor system that automatically provides useful data products. Typically, a SensorWeb is comprised of heterogeneous sensors tied together with a messaging architecture and web services. This paper provides an overview of the various technologies that were tested and eventually folded into normal operations. As these technologies were folded in, the nature of operations transformed. The SensorWeb software enables easy connectivity for collaboration with sensors, but the side benefit is that it improved the EO-1 operational efficiency. This paper presents the various phases of EO-1 operation over the past 12 years and also presents operational efficiency gains demonstrated by some metrics.

Mandl, Daniel↗

NASA NTRS2012

Developing an Open Source, Reusable Platform for Distributed Collaborative Information Management in the Early Detection Research Network

For the past decade, the NASA Jet Propulsion Laboratory, in collaboration with Dartmouth University has served as the center for informatics for the Early Detection Research Network (EDRN). The EDRN is a multi-institution research effort funded by the U.S. National Cancer Institute (NCI) and tasked with identifying and validating biomarkers for the early detection of cancer. As the distributed network has grown, increasingly formal processes have been developed for the acquisition, curation, storage, and dissemination of heterogeneous research information assets, and an informatics infrastructure has emerged. In this paper we discuss the evolution of EDRN informatics, its success as a mechanism for distributed information integration, and the potential sustainability and reuse benefits of emerging efforts to make the platform components themselves open source. We describe our experience transitioning a large closed-source software system to a community driven, open source project at the Apache Software Foundation, and point to lessons learned that will guide our present efforts to promote the reuse of the EDRN informatics infrastructure by a broader community.

Early Detection Research Network (EDRN)↗

NASA NTRS1989

Integrating NASA's Land Analysis System (LAS) image processing software with an appropriate Geographic Information System (GIS): A review of candidates in the public domain

A user requirements analysis (URA) was undertaken to determine and appropriate public domain Geographic Information System (GIS) software package for potential integration with NASA's LAS (Land Analysis System) 5.0 image processing system. The necessity for a public domain system was underscored due to the perceived need for source code access and flexibility in tailoring the GIS system to the needs of a heterogenous group of end-users, and to specific constraints imposed by LAS and its user interface, Transportable Applications Executive (TAE). Subsequently, a review was conducted of a variety of public domain GIS candidates, including GRASS 3.0, MOSS, IEMIS, and two university-based packages, IDRISI and KBGIS. The review method was a modified version of the GIS evaluation process, development by the Federal Interagency Coordinating Committee on Digital Cartography. One IEMIS-derivative product, the ALBE (AirLand Battlefield Environment) GIS, emerged as the most promising candidate for integration with LAS. IEMIS (Integrated Emergency Management Information System) was developed by the Federal Emergency Management Agency (FEMA). ALBE GIS is currently under development at the Pacific Northwest Laboratory under contract with the U.S. Army Corps of Engineers' Engineering Topographic Laboratory (ETL). Accordingly, recommendations are offered with respect to a potential LAS/ALBE GIS linkage and with respect to further system enhancements, including coordination with the development of the Spatial Analysis and Modeling System (SAMS) GIS in Goddard's IDM (Intelligent Data Management) developments in Goddard's National Space Science Data Center.

Rochon, Gilbert L.↗

NASA NTRS2019

Integrated support of NASA satellite and in situ oceanographic data via the PO.DAAC

The NASA Physical Oceanography DAAC (PO.DAAC) serves as one of the premier repositories for oceanographic satellite data. More recently, however, it is also increasingly archiving and distributing complementary in situ datasets from NASA-sponsored field campaigns. Here we present an overview of these projects, the complex multivariate data they produce, and some of the data interoperability challenges faced when dealing with such a heterogeneous suite of observations. We summarize the range of online tools and services currently available via the PODAAC, including data discovery services, web-services for subsetting/extraction, compliance checking and visualization. We also preview some new capabilities under development that may feature in future. These efforts are indicative of an evolution of DAAC services in pursuit of our broader vision: a more integrated approach to multi-sensor oceanographic data access and delivery spanning NASA satellite missions and field campaigns in support of science and applications for societal benefit.

Vannan, Suresh↗

NASA NTRS1991

Framework Programmable Platform for the Advanced Software Development Workstation: Preliminary system design document

The Framework Programmable Software Development Platform (FPP) is a project aimed at combining effective tool and data integration mechanisms with a model of the software development process in an intelligent integrated software environment. Guided by the model, this system development framework will take advantage of an integrated operating environment to automate effectively the management of the software development process so that costly mistakes during the development phase can be eliminated. The focus here is on the design of components that make up the FPP. These components serve as supporting systems for the Integration Mechanism and the Framework Processor and provide the 'glue' that ties the FPP together. Also discussed are the components that allow the platform to operate in a distributed, heterogeneous environment and to manage the development and evolution of software system artifacts.

Mayer, Richard J.↗

NASA NTRSDate not supplied

Bridging the Last Mile with Open-Source Advancements: Empowering Communities through Fusion of Aerosol Optical Depth (AOD) Products from Multi-Satellite Sensors

Aerosol Optical Depth (AOD) is a crucial parameter for understanding atmospheric aerosol distribution and their impact on climate and air quality. With the growing number of Earth observation satellites, there is an abundance of AOD products derived from various sensors onboard both geostationary and low-orbit satellites. The availability of multiple datasets provides an opportunity to harness the strengths of each sensor and create comprehensive and accurate AOD datasets for climate and air quality studies at different temporal and spatial scales. Our NASA aerosol MEaSURES project has made significant strides in recent years by undertaking the ambitious task of developing an open-source package tailored for fusing AOD products from different sources. The package is based on OOP (Object-Oriented Programming) design and is implemented in Python modules. Generic interfaces enable easy inclusion of large and heterogeneous data. The package may be utilized to produce harmonized AOD datasets with enhanced spatial and temporal coverage. The latest version of the package is able to process and integrate the dark-target AOD data from six different sensors: AHI Himawari-8, ABI GOES-West, ABI GOES-East, MODIS AQUA, MODIS TERRA, and VIIRS SNPP. Rigorous validation and intercomparison studies have been performed to assess the accuracy and reliability of the fused AOD product against ground-based measurements and reference datasets. The open-source nature of the developed package ensures transparency, reproducibility, and community engagement. The research community and stakeholders can access, contribute to, and further improve the fusion methodology, making it adaptable to other studies, or expanding it to include new satellite data as they become available. In this poster presentation, we will introduce the accomplishments and challenges faced during the development of the open-source package for AOD data fusion, and demonstrate the advantages of combining AOD products from the six aforementioned satellite sensors. The presentation aims to foster discussions, collaborations, and future directions in integrating Earth observation and remote sensing data, which may contribute to a better understanding of atmospheric aerosols and their impacts on our environment.

Zhaohui Zhang↗

NASA NTRS2005

A Framework for Integration of IVHM Technologies for Intelligent Integration for Vehicle Management

As a part of the overall goal of developing Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of IIVM. These real-time responses allow the IIVM to modify the effected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for IIVH includes: 1) robust controllers for use in re-usable launch vehicles, 2) scaleable/flexible computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project. The integration of these IVHM technologies forms the framework for IIVM.

Paris, Deidre E.↗

NASA NTRS2015

Operator Informational Needs for Multiple Autonomous Small Vehicles

With the anticipated explosion of small unmanned aerial vehicles, it is highly likely that operators will be controlling fleets of autonomous vehicles. To fulfill the promise of autonomy, vehicle operators will not be concerned with manual control of the vehicle; instead, they will deal with the overall mission. Furthermore, the one operator to many vehicles is becoming a constant meme with various industries including package delivery, search and rescue, and utility companies. In order for an operator to concurrently control several vehicles, his station must look and behave very differently than the current ground control station instantiations. Furthermore, the vehicle will have to be much more autonomous, especially during non-normal operations, in order to accommodate the knowledge deficit or the information overload of the operator in charge of several vehicles. The expected usage increase of small drones requires presenting the operational information generated by a fleet of heterogeneous autonomous agents to an operator. NASA Langley Research Center's Autonomy Incubator has brought together researchers in various disciplines including controls, trajectory planning, systems engineering, and human factors to develop an integrated system to study autonomy issues. The initial human factors effort is focusing on mission displays that would give an operator the overall status of all autonomous agents involved in the current mission. This paper will discuss the specifics of the mission displays for operators controlling several vehicles.

Trujillo, Anna C.↗

NASA NTRS2009

Work Coordination Engine

The Work Coordination Engine (WCE) is a Java application integrated into the Service Management Database (SMDB), which coordinates the dispatching and monitoring of a work order system. WCE de-queues work orders from SMDB and orchestrates the dispatching of work to a registered set of software worker applications distributed over a set of local, or remote, heterogeneous computing systems. WCE monitors the execution of work orders once dispatched, and accepts the results of the work order by storing to the SMDB persistent store. The software leverages the use of a relational database, Java Messaging System (JMS), and Web Services using Simple Object Access Protocol (SOAP) technologies to implement an efficient work-order dispatching mechanism capable of coordinating the work of multiple computer servers on various platforms working concurrently on different, or similar, types of data or algorithmic processing. Existing (legacy) applications can be wrapped with a proxy object so that no changes to the application are needed to make them available for integration into the work order system as "workers." WCE automatically reschedules work orders that fail to be executed by one server to a different server if available. From initiation to completion, the system manages the execution state of work orders and workers via a well-defined set of events, states, and actions. It allows for configurable work-order execution timeouts by work-order type. This innovation eliminates a current processing bottleneck by providing a highly scalable, distributed work-order system used to quickly generate products needed by the Deep Space Network (DSN) to support space flight operations. WCE is driven by asynchronous messages delivered via JMS indicating the availability of new work or workers. It runs completely unattended in support of the lights-out operations concept in the DSN.

Zendejas, Silvino↗

NASA NTRS1993

Alveolar ventilation to perfusion heterogeneity and diffusion impairment in a mathematical model of gas exchange

This study describes a two-compartment model of pulmonary gas exchange in which alveolar ventilation to perfusion (VA/Q) heterogeneity and impairment of pulmonary diffusing capacity (D) are simultaneously taken into account. The mathematical model uses as input data measurements usually obtained in the lung function laboratory. It consists of two compartments and an anatomical shunt. Each compartment receives fractions of alveolar ventilation and blood flow. Mass balance equations and integration of Fick's law of diffusion are used to compute alveolar and blood O2 and CO2 values compatible with input O2 uptake and CO2 elimination. Two applications are presented. The first is a method to partition O2 and CO2 alveolar-arterial gradients into VA/Q and D components. The technique is evaluated in data of patients with chronic obstructive pulmonary disease (COPD). The second is a theoretical analysis of the effects of blood flow variation in alveolar and blood O2 partial pressures. The results show the importance of simultaneous consideration of D to estimate VA/Q heterogeneity in patients with diffusion impairment. This factor plays an increasing role in gas alveolar-arterial gradients as severity of COPD increases. Association of VA/Q heterogeneity and D may produce an increase of O2 arterial pressure with decreasing QT which would not be observed if only D were considered. We conclude that the presented computer model is a useful tool for description and interpretation of data from COPD patients and for performing theoretical analysis of variables involved in the gas exchange process.

NASA Discipline Environmental Health↗

NASA NTRS1994

Perception system and functions for autonomous navigation in a natural environment

This paper presents the approach, algorithms, and processes we developed for the perception system of a cross-country autonomous robot. After a presentation of the tele-programming context we favor for intervention robots, we introduce an adaptive navigation approach, well suited for the characteristics of complex natural environments. This approach lead us to develop a heterogeneous perception system that manages several different terrain representatives. The perception functionalities required during navigation are listed, along with the corresponding representations we consider. The main perception processes we developed are presented. They are integrated within an on-board control architecture we developed. First results of an ambitious experiment currently underway at LAAS are then presented.

Chatila, Raja↗

NASA NTRS1983

Human capabilities: Long residence - An uncharted field

In the context of the planned NASA space station, it is anticipated that a number of problems will be posed by permanent residence in space. Not only will the intensive training which has characterized earlier manned programs diminish under the pressure of increased launch rates, but the new and larger crews will socially, educationally, psychologically and physiologically constitute a far more heterogeneous group than those of the past. In addition, advanced computer technology will result in a degree of reliance on onboard data processing which will alter the relations of ground and space operators, requiring careful integration of people and technologies. Attention is given to questions of food, robotics, extravehicular activity, hygiene and environmental noise.

Chambers, A.↗

NASA NTRS2019

Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land-Atmosphere Coupling

The role of soil moisture in NWP has gained more attention in recent years, as studies have demonstrated impacts of land surface states on ambient weather from diurnal to seasonal scales. However, soil moisture initialization approaches in coupled models remain quite diverse in terms of their complexity and observational roots, while assessment using bulk forecast statistics can be simplistic and misleading. In this study, a suite of soil moisture initialization approaches is used to generate short-term coupled forecasts over the U.S. Southern Great Plains using NASA’s Land Information System (LIS) and NASA Unified WRF (NU-WRF) modeling systems. This includes a wide range of currently used initialization approaches, including soil moisture derived from ‘off-the-shelf’ products such as atmospheric models and land data assimilation systems, high-resolution land surface model spinups, and satellite-based soil moisture products from SMAP. Results indicate that the spread across initialization approaches can be quite large in terms of soil moisture conditions and spatial resolution, and that SMAP performs well in terms of heterogeneity and temporal dynamics when compared against high resolution land surface model and in-situ soil moisture estimates. Case studies are analyzed using the local land-atmosphere coupling (LoCo) framework that relies on integrated assessment of soil moisture, surface flux, boundary layer, and ambient weather, with results highlighting the critical role of inherent model background biases. In addition, simultaneous assessment of land vs. atmospheric initial conditions in an integrated, process-level fashion can help address the question of whether improvements in traditional NWP verification statistics are achieved for the right reasons.

Southern Great Plains↗

NASA NTRSDate not supplied

Flight Testing of In-Time Safety Assurance Technologies for UAS Operations

Ongoing research at NASA is driven by a strategic plan defined by the Aeronautics Research Mission Directorate and a vision for future In-Time Aviation Safety Management Systems (IASMS) as described by the National Academies. In both visions, system safety awareness and provision are expanded through increased access to relevant data; integrated analysis and predictive capabilities; improved real-time detection and alerting of domain-specific hazards; decision support, and in some cases, automated risk mitigation strategies. One primary research focus is to develop means by which more timely (i.e., “in-time”) actions may be taken to mitigate precursors, anomalies, or trends that are observed during operations. In this paper, we describe such means as a collection of Services, Functions, and Capabilities (SFCs) that are supported by an underlying information system. For example, an integrated risk assessment capability is envisioned that continuously monitors safety-related metrics and margins and recommends timely operational changes. Assessment functions and/or services can be based on data analytics and predictive models derived from heterogeneous data sets that span relevant indicator metrics and their time histories. Likewise, on-board functions can identify and reduce susceptibility to precursor conditions that have led (and can lead) to aircraft loss-of-control or out-of-control accidents. This paper summarizes development and testing of such an information system tailored to hazards anticipated for future highly autonomous flight missions near and over densely populated areas. Testing is accomplished via simulation and by using small, unmanned aircraft operating over a test range at NASA’s Langley Research Center. Flight plans and test scenarios are defined to emulate several use-cases, including package delivery; reconnaissance; fire management; and urban air taxi vertiport operations. Two test phases are summarized with Phase 1 occurring in (2019-2020) and Phase 2 ongoing (2021-present). Results focus on SFC performance, technology readiness level assessment, and requirements discovery/validation. Companion papers are cited throughout for additional details on the recent testing.

safety management↗