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At least 703 records · Page 39

Development of a Software Tool to Automate ADCO Flight Controller Console Planning Tasks

This independent study project covers the development of the International Space Station (ISS) Attitude Determination and Control Officer (ADCO) Planning Exchange APEX Tool. The primary goal of the tool is to streamline existing manual and time-intensive planning tools into a more automated, user-friendly application that interfaces with existing products and allows the ADCO to produce accurate products and timelines more effectively. This paper will survey the current ISS attitude planning process and its associated requirements, goals, documentation and software tools and how a software tool could simplify and automate many of the planning actions which occur at the ADCO console. The project will be covered from inception through the initial prototype delivery in November 2011 and will include development of design requirements and software as well as design verification and testing.

Anderson, Mark G.↗

Onboard Short Term Plan Viewer

Onboard Short Term Plan Viewer (OSTPV) is a computer program for electronic display of mission plans and timelines, both aboard the International Space Station (ISS) and in ISS ground control stations located in several countries. OSTPV was specifically designed both (1) for use within the limited ISS computing environment and (2) to be compatible with computers used in ground control stations. OSTPV supplants a prior system in which, aboard the ISS, timelines were printed on paper and incorporated into files that also contained other paper documents. Hence, the introduction of OSTPV has both reduced the consumption of resources and saved time in updating plans and timelines. OSTPV accepts, as input, the mission timeline output of a legacy, print-oriented, UNIX-based program called "Consolidated Planning System" and converts the timeline information for display in an interactive, dynamic, Windows Web-based graphical user interface that is used by both the ISS crew and ground control teams in real time. OSTPV enables the ISS crew to electronically indicate execution of timeline steps, launch electronic procedures, and efficiently report to ground control teams on the statuses of ISS activities, all by use of laptop computers aboard the ISS.

Hall, Tim↗

Engineering Technical Review Planning Briefing

The general topics covered in the engineering technical planning briefing are 1) overviews of NASA, Marshall Space Flight Center (MSFC), and Engineering, 2) the NASA Systems Engineering(SE) Engine and its implementation , 3) the NASA Project Life Cycle, 4) MSFC Technical Management Branch Services in relation to the SE Engine and the Project Life Cycle , 5) Technical Reviews, 6) NASA Human Factor Design Guidance , and 7) the MSFC Human Factors Team. The engineering technical review portion of the presentation is the primary focus of the overall presentation and will address the definition of a design review, execution guidance, the essential stages of a technical review, and the overall review planning life cycle. Examples of a technical review plan content, review approaches, review schedules, and the review process will be provided and discussed. The human factors portion of the presentation will focus on the NASA guidance for human factors. Human factors definition, categories, design guidance, and human factor specialist roles will be addressed. In addition, the NASA Systems Engineering Engine description, definition, and application will be reviewed as background leading into the NASA Project Life Cycle Overview and technical review planning discussion.

Gardner, Terrie↗

Automated Planning of Science Products Based on Nadir Overflights and Alerts for Onboard and Ground Processing

A set of automated planning algorithms is the current operations baseline approach for the Intelligent Payload Module (IPM) of the proposed Hyper spectral Infrared Imager (HyspIRI) mission. For this operations concept, there are only local (e.g. non-depletable) operations constraints, such as real-time downlink and onboard memory, and the forward sweeping algorithm is optimal for determining which science products should be generated onboard and on ground based on geographical overflights, science priorities, alerts, requests, and onboard and ground processing constraints. This automated planning approach was developed for the HyspIRI IPM concept. The HyspIRI IPM is proposed to use an X-band Direct Broadcast (DB) capability that would enable data to be delivered to ground stations virtually as it is acquired. However, the HyspIRI VSWIR and TIR instruments will produce approximately 1 Gbps data, while the DB capability is 15 Mbps for a approx. =60X oversubscription. In order to address this mismatch, this innovation determines which data to downlink based on both the type of surface the spacecraft is overflying, and the onboard processing of data to detect events. For example, when the spacecraft is overflying Polar Regions, it might downlink a snow/ice product. Additionally, the onboard software will search for thermal signatures indicative of a volcanic event or wild fire and downlink summary information (extent, spectra) when detected, thereby reducing data volume. The planning system described above automatically generated the IPM mission plan based on requested products, the overflight regions, and available resources.

Chien, Steve A.↗

RECOVER: An Automated Cloud-Based Decision Support System for Post-fire Rehabilitation Planning

RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.

cloud computing↗

Autonomous Spacecraft Communication Interface for Load Planning

Ground-based controllers can remain in continuous communication with spacecraft in low Earth orbit (LEO) with near-instantaneous communication speeds. This permits near real-time control of all of the core spacecraft systems by ground personnel. However, as NASA missions move beyond LEO, light-time communication delay issues, such as time lag and low bandwidth, will prohibit this type of operation. As missions become more distant, autonomous control of manned spacecraft will be required. The focus of this paper is the power subsystem. For present missions, controllers on the ground develop a complete schedule of power usage for all spacecraft components. This paper presents work currently underway at NASA to develop an architecture for an autonomous spacecraft, and focuses on the development of communication between the Mission Manager and the Autonomous Power Controller. These two systems must work together in order to plan future load use and respond to unanticipated plan deviations. Using a nominal spacecraft architecture and prototype versions of these two key components, a number of simulations are run under a variety of operational conditions, enabling development of content and format of the messages necessary to achieve the desired goals. The goals include negotiation of a load schedule that meets the global requirements (contained in the Mission Manager) and local power system requirements (contained in the Autonomous Power Controller), and communication of off-plan disturbances that arise while executing a negotiated plan. The message content is developed in two steps: first, a set of rapid-prototyping "paper" simulations are preformed; then the resultant optimized messages are codified for computer communication for use in automated testing.

Controls↗

Spitzer Mission Operation System Planning for IRAC Warm-Instrument Characterization

This paper will describe how the Spitzer Mission Operations System planned and executed the characterization phase between Spitzer's cryogenic mission and its warm mission. To the largest extend possible, the execution of this phase was done with existing processing and procedures. The modifications that were made were in response to the differences of the characterization phase compared to normal phases before and after. The primary two categories of difference are: unknown date of execution due to uncertainty of knowledge of the date of helium depletion, and the short cycle time for data analysis and re-planning during execution. In addition, all of the planning and design had to be done in parallel with normal operations, and we had to transition smoothly back to normal operations following the transition. This paper will also describe the re-planning we had to do following an anomaly discovered in the first days after helium depletion.

IWIC↗

Probabilistic Motion Planning of Balloons in Strong, Uncertain Wind Fields

This paper introduces a new algorithm for probabilistic motion planning in arbitrary, uncertain vector fields, with emphasis on high-level planning for Montgolfiere balloons in the atmosphere of Titan. The goal of the algorithm is to determine what altitude--and what horizontal actuation, if any is available on the vehicle--to use to reach a goal location in the fastest expected time. The winds can vary greatly at different altitudes and are strong relative to any feasible horizontal actuation, so the incorporation of the winds is critical for guidance plans. This paper focuses on how to integrate the uncertainty of the wind field into the wind model and how to reach a goal location through the uncertain wind field, using a Markov decision process (MDP). The resulting probabilistic solutions enable more robust guidance plans and more thorough analysis of potential paths than existing methods.

Wolf, Michael T.↗

Cassini Information Management System in Distributed Operations Collaboration and Cassini Science Planning

Launched on October 15, 1997, the Cassini-Huygens spacecraft began its ambitious journey to the Saturnian system with a complex suite of 12 scientific instruments, and another 6 instruments aboard the European Space Agencies Huygens Probe. Over the next 6 1/2 years, Cassini would continue its relatively simplistic cruise phase operations, flying past Venus, Earth, and Jupiter. However, following Saturn Orbit Insertion (SOI), Cassini would become involved in a complex series of tasks that required detailed resource management, distributed operations collaboration, and a data base for capturing science objectives. Collectively, these needs were met through a web-based software tool designed to help with the Cassini uplink process and ultimately used to generate more robust sequences for spacecraft operations. In 2001, in conjunction with the Southwest Research Institute (SwRI) and later Venustar Software and Engineering Inc., the Cassini Information Management System (CIMS) was released which enabled the Cassini spacecraft and science planning teams to perform complex information management and team collaboration between scientists and engineers in 17 countries. Originally tailored to help manage the science planning uplink process, CIMS has been actively evolving since its inception to meet the changing and growing needs of the Cassini uplink team and effectively reduce mission risk through a series of resource management validation algorithms. These algorithms have been implemented in the web-based software tool to identify potential sequence conflicts early in the science planning process. CIMS mitigates these sequence conflicts through identification of timing incongruities, pointing inconsistencies, flight rule violations, data volume issues, and by assisting in Deep Space Network (DSN) coverage analysis. In preparation for extended mission operations, CIMS has also evolved further to assist in the planning and coordination of the dual playback redundancy of highvalue data from targets such as Titan and Enceladus. This paper will outline the critical role that CIMS has played for Cassini in the distributed ops paradigm throughout operations. This paper will also examine the evolution that CIMS has undergone in the face of new science discoveries and fluctuating operational needs. And finally, this paper will conclude with theoretical adaptation of CIMS for other projects and the potential savings in cost and risk reduction that could potentially be tapped into by future missions.

Equils, Douglas J.↗

Development of Level 2 Calibration and Validation Plans for GOES-R; What is a RIMP?

Calibration and Validation (CalVal) plans for Geostationary Operational Environmental Satellite version R (GOES-R) Level 2 (L2) products were documented via Resource, Implementation, and Management Plans (RIMPs) for all of the official L2 products required from the GOES-R Advanced Baseline Imager (ABI). In 2015 the GOES-R program decided to replace the typical CalVal plans with RIMPs that covered, for a given L2 product, what was required from that product, how it would be validated, and what tools would be used to do so. Similar to Level 1b products, the intent was to cover the full spectrum of planning required for the CalVal of L2 ABI products. Instead of focusing on step-by-step procedures, the RIMPs concentrated on the criteria for each stage of the validation process (Beta, Provisional, and Full Validation) and the many elements required to prove when each stage was reached.

Validation↗

Development of Level 2 Calibration and Validation Plans for GOES-R; What is a RIMP?

Calibration and Validation (CalVal) plans for Geostationary Operational Environmental Satellite version R (GOES-R) Level 2 (L2) products were documented via Resource, Implementation, and Management Plans (RIMPs) for all of the official L2 products required from the GOES-R Advanced Baseline Imager (ABI). In 2015 the GOES-R program decided to replace the typical CalVal plans with RIMPs that covered, for a given L2 product, what was required from that product, how it would be validated, and what tools would be used to do so. Similar to Level 1b products, the intent was to cover the full spectrum of planning required for the CalVal of L2 ABI products. Instead of focusing on step-by-step procedures, the RIMPs concentrated on the criteria for each stage of the validation process (Beta, Provisional, and Full Validation) and the many elements required to prove when each stage was reached.

Validation↗

Assessing Ecosystem Service Provision Under Climate Change to Support Conservation and Development Planning in Myanmar

Inclusion of ecosystem services (ES) information into national-scale development and climate adaptation planning has yet to become common practice, despite demand from decision makers. Identifying where ES originate and to whom the benefits flowunder current and future climate conditionsis especially critical in rapidly developing countries, where the risk of ES loss is high. Here, using Myanmar as a case study, we assess where and how ecosystems provide key benefits to the countrys people and infrastructure. We model the supply of and demand for sediment retention, dry-season baseflows, flood risk reduction and coastal storm protection from multiple beneficiaries. We find that locations currently providing the greatest amount of services are likely to remain important under the range of climate conditions considered, demonstrating their importance in planning for climate resilience. Overlap between priority areas for ES provision and biodiversity conservation is higher than expected by chance overall, but the areas important for multiple ES are underrepresented in currently designated protected areas and Key Biodiversity Areas. Our results are contributing to development planning in Myanmar, and our approach could be extended to other contexts where there is demand for national-scale natural capital information to shape development plans and policies

Climate change↗

NASA's Advanced Extra-Vehicular Activity Space Suit Pressure Garment 2018 Status and Development Plan

This paper presents both near-term and long-term NASA Advanced Extra-vehicular Activity (EVA) Pressure Garment development efforts. The near-term plan discusses the development of pressure garment components for the first design iteration of the International Space Station exploration space suit demonstration configuration, termed the xEMU Demo. The xEMU Demo effort is targeting a 2023-2025 flight demonstration timeframe. The Fiscal Year 2018 (FY18) tasks focus on either the initiation or maturation of component design, depending on the state of development of the components, and the assembly of a suit configuration, termed Z-2.5, that will be used to evaluate changes to the upper torso geometry in a Neutral Buoyancy Laboratory (NBL) test series. The geometry changes, which are being driven by the need to reduce the front-to-back dimension of the advanced extravehicular mobility unit, diverge from a proven shape, such as that of the Mark III Space Suit Technology Demonstrator. The 2018 efforts culminate in the Z-2.5 NBL test. The lessons learned from the Z-2.5 NBL test will inform the xEMU Demo design as the effort moves toward design verification testing and preliminary and critical design reviews. The long-term development plan looks to surface exploration and operations. Technology and knowledge gaps exist between the xEMU Demo configuration; a lunar surface capability, xEMU; and Mars surface suit, mEMU. The development plan takes into account both the priority and the anticipated development duration for each particular technology. The long-term development plan will be updated as risks are mitigated and gaps are closed, but its overarching structure will remain intact.

space suit↗

Online Multi-Modal Learning and Adaptive Information Trajectory Planning for Autonomous Exploration

In robotic information gathering missions, scientists are typically interested in understanding variables which require proxy measurements from specialized sensor suites to estimate. However, energy and time constraints limit how often these sensors can be used in a mission. Robots are also equipped with cheaper to use navigation sensors such as cameras. In this paper, we explore a challenging planning problem in which a robot is required to learn about a scientific variable of interest in an initially unknown environment by planning informative paths and deciding when and where to use its sensors. To tackle this we present two innovations: a Bayesian generative model framework to automatically learn correlations between expensive science sensors and cheaper to use navigation sensors online, and a sampling based approach to plan for multiple sensors while handling long horizons and budget constraints. Our approach does not grow in complexity with data and is anytime making it highly applicable to field robotics. We tested our approach extensively in simulation and validated it with real data collected during the 2014 Mojave Volatiles Prospector Mission. Our planning algorithm performs statistically significantly better than myopic approaches and at least as well as a coverage-based algorithm in an initially unknown environment while having added advantages of being able to exploit prior knowledge and handle other intricacies of the real world without further algorithmic modifications.

learning↗

Designing and Building a Crew-Centric Mobile Scheduling and Planning Tool for Exploring Crew Autonomy Concepts Onboard the International Space Station

During 2015, as part of our ongoing research on crew autonomy, our team adapted and extended the plan viewing tool, Playbook, into a mobile tool for exploring crew autonomy onboard the International Space Station (ISS). This work enables crewmembers to intuitively re-plan and schedule on their own with limited input from mission control. Designed for ease of use, re-planning is composed of simple drag and drop interactions and learning the tool requires little to no training. Playbook was successfully uplinked onto ISS as a technology demonstration and completed its onboard ground and crew checkouts in August and September 2015, respectively. We will discuss and describe how Playbook was able to integrate with actual ISS operational plans and operational procedures without disrupting real mission operations. This work will also outline the design and technical constraints required to build a collaborative tool that allows multiple users to simultaneously self-schedule and synchronize during communication dropouts in the restricted networking and computing environment onboard ISS. Finally, we will explore the aspects of crew autonomy that this technology enables as well as discuss our next steps and possible extensions.

ISS↗

Activity Planning for a Lunar Orbital Mission

This paper describes a challenging, real-world planning problem within the context of a NASA mission called LADEE (Lunar Atmospheric Dust Environment Explorer). LADEEs science phase was performed in an equatorial, retrograde orbit around the Moon. The science observations were constrained with respect to key points in the spacecrafts orbit. We present the approach taken to reduce the complexity of the activity planning task in order to effectively perform it within the time pressures imposed by the mission requirements. One key aspect of this approach is the design of the activity planning process based on principles of problem decomposition and planning abstraction levels. The second key aspect is the mixed-initiative system developed for this task, called LASS (LADEE Activity Scheduling System). The primary challenge for LASS was representing and managing the orbit-based science constraints, given their dynamic nature due to the continually updated orbit determination solution.

Bresina, John L.↗

STF-1 Ground Operations - Automating the Planning, Scheduling, Assessment and Data Processing/Reduction for a Small Satellite

On December 16, 2018, a 3-U CubeSat named STF-1 launched as West Virginia's first spacecraft. This event marked the culmination of a run-up to launch involving the production of the spacecraft, creation/configuration of command and control infrastructure, and the evolution of its co-creation, the NASA Operational Simulator for Small Satellites (NOS3). This event also marked the beginning of a new phase: operations. While plans, procedures, and infrastructure were already in place or started for operations, many lessons were learned during the operations phase, especially during early operations (first month/commissioning phase). Additional plans, procedures, and infrastructure, especially related to communication planning and automated data processing, were created and developed to fill needs for the operation of the STF-1 mission.This paper and presentation will overview the STF-1 operations team's solutions to addressing the many needs of operating a low-earth orbiting CubeSat mission with a single ground antenna that is shared and scheduled with several other missions. The STF-1 operations team deployed a combination of virtualization technologies, ground station technology solutions, collaboration software, custom planning software solutions, and existing ground antenna scheduling solutions to create an effective and efficient CubeSat operations environment. The end-solution satisfied the operations stakeholders, which include NASA, its industry partner TMC2 Technologies, and four independent professor-student teams at West Virginia University.

Suder, Mark↗

Conducting Efficient Remote Science and Planning Operations for Ocean Exploration Using Exploration Ground Data Systems (xGDS)

NASA Ames’ Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade. In the last two years, we have participated in SUBSEA, a multi-institution collaborative project*. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC)**. In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule. The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team’s ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. * SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA’s Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island’s Graduate School of Oceanography (GSO).

Cohen, Tamar E.↗