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This viewgraph presentation reviews the phase I plan of the prototype of the IMMR by the Multilateral Medical Operations Panel (MMOP) Medical Informatics & Technology (MIT) Working Group. It reviews the Purpose of IMMR Prototype Phase 1 (IPP1); the IPP1 Plan Overview, the IMMR Prototype Phase 1 Plan for PDDs and MIC and MIC-DDs, Plan for MICs, a nd the IPP1 objectives
The Solar Dynamics Observatory (SDO) is planned to launch in early 2009 as a mission to study the solar variability and its impact on Earth. To best satisfy its science goal, SDO will fly in a geosynchronous orbit with an inclination of approximately 29 deg. The spacecraft attitude is designed so that the science instruments point directly at the Sun with high accuracy. One of SDO's principal requirements is to obtain long periods of uninterrupted observations. The observations have an extremely high data volume so SDO must be in continuous contact with the ground during the observation periods. To maintain this contact, SDO is equipped with a pair of high gain antennas (HGAs) transmitting to a pair of ground antennas at the SDO ground station (SDOGS) located in White Sands, New Mexico. Either HGA can transmit to either SDOGS antenna. Neither HGA can be powered down. During a portion of each year, each of the HGA beams will intersect with the SDO body for a portion of the orbit. The original SDO antenna contact plan used each HGA for the half of each year during which its beam would not intersect the spacecraft. No data would be lost except, possibly, when switching from one antenna to another. After this plan was adopted, further analysis showed that daily handovers would be necessary for significant periods of the year. This unexpected need for extensive handovers necessitated that a handover design be developed to minimize the impact on the mission. This antenna handover design was developed and successfully tested with simulated data using the slew rate limits from preliminary jitter analysis. Subsequent analysis provided significant revision of allowed rates requiring modification of the handover plans.
NASA is planning an engineering telemetry demonstration with Mars Reconnaissance Orbiter (MRO). Capabilities of Ka-band (32 GHz) for use with deep space mission are demonstrated using the link optimization algorithms and weather forecasting. Furthermore, based on the performance of previous deep space missions with Ka-band downlink capabilities, experiment plans are developed for telemetry operations during superior solar conjunction. A general overview of the demonstration is given followed by a description of the mission planning during cruise, the primary science mission and superior conjunction. As part of the primary science mission planning the expected data return for various data optimization methods is calculated. These results indicate that, given MRO's data rates, a link optimized to use of at most two data rates, subject to a minimum availability of 90%, performs almost as well as a link with no limits on the number of data rates subject to the same minimum availability.
Systems and methods are provided for an integrated graphical user interface which facilitates the display and editing of aircraft flight-plan data. A user (e.g., a pilot) located within the aircraft provides input to a processor through a cursor control device and receives visual feedback via a display produced by a monitor. The display includes various graphical elements associated with the lateral position, vertical position, flight-plan and/or other indicia of the aircraft's operational state as determined from avionics data and/or various data sources. Through use of the cursor control device, the user may modify the flight-plan and/or other such indicia graphically in accordance with feedback provided by the display. In one embodiment, the display includes a lateral view, a vertical profile view, and a hot-map view configured to simplify the display and editing of the aircraft's flight-plan data.
The Solar Dynamics Observatory (SDO) is planned to launch in early 2009 as a mission to study the solar variability and its impact on Earth. To best satisfy its science goal, SDO will fly in a geosynchronous orbit with an inclination of approximately 29 deg. The spacecraft attitude is designed so that the science instruments point directly at the Sun with high accuracy. One of SDO s principal requirements is to obtain long periods of uninterrupted observations. The observations have an extremely high data volume so SDO must be in continuous contact with the ground during the observation periods. To maintain this contact, SDO is equipped with a pair of high gain antennas (HGAs) transmitting to a pair of ground antennas at the SDO ground station (SDOGS) located in White Sands, New Mexico. Either HGA can transmit to either SDOGS antenna. Neither HGA can be powered down. During a portion of each year, each of the HGA beams will intersect with the SDO body for a portion of the orbit. The original SDO antenna contact plan used each HGA for the half of each year during which its beam would not intersect the spacecraft. No data would be lost except, possibly, when switching from one antenna to another. After this plan was adopted, further analysis showed that daily handovers would be necessary for significant periods of the year. This unexpected need for extensive handovers necessitated that a handover design be developed to minimize the impact on the mission. This antenna handover design was developed and successfully tested with simulated data using the slew rate limits from preliminary jitter analysis. Subsequent analysis provided significant revision of allowed rates requiring modification of the handover plans.
The purpose of this document is to identify the general flight/mission planning requirements for same-day file-and-fly access to the NAS for both civil and military High-Altitude Long Endurance (HALE) Unmanned Aircraft System (UAS). Currently the scope of this document is limited to Step 1, operations above flight level 43,000 feet (FL430). This document describes the current applicable mission planning requirements and procedures for both manned and unmanned aircraft and addresses HALE UAS flight planning considerations in the future National Airspace System (NAS). It also discusses the unique performance and operational capabilities of HALE UAS associated with the Access 5 Project, presents some of the projected performance characteristics and conceptual missions for future systems, and provides detailed analysis of the recommended mission planning elements for operating HALE UAS in the NAS.
The Aeronautics Test Program (ATP) within the National Aeronautics and Space Administration (NASA) Aeronautics Research Mission Directorate (ARMD) initiated a strategic planning effort to re-vitalize the force measurement capability within NASA. The team responsible for developing the plan included members from three NASA Centers (Langley, Ames and Glenn) as well as members from the Air Force s Arnold Engineering and Development Center (AEDC). After visiting and discussing force measurement needs and current capabilities at each participating facility as well as selected force measurement companies, a strategic plan was developed to guide future NASA investments. This paper will provide the details of the strategic plan and include asset management, organization and technology research and development investment priorities as well as efforts to date.
The Education Enterprise Strategy, the expanding knowledge of how people learn, and the community-wide interest in revolutionizing Earth and space science education have guided us in developing this plan for Earth science education. This document builds on the success of the first plan for Earth science education published in 1996; it aligns with the new framework set forth in the NASA Education Enterprise Strategy; it recognizes the new educational opportunities resulting from research programs and flight missions; and it builds on the accomplishments th'at the Earth Science Enterprise has made over the last decade in studying Earth as a system. This document embodies comprehensive, practicable plans for inspiring our children; providing educators with the tools they need to teach science, technology, engineering, and mathematics (STEM); and improving our citizens' scientific literacy. This plan describes an approach to systematically sharing knowledge; developing the most effective mechanisms to achieve tangible, lasting results; and working collaboratively to catalyze action at a scale great enough to ensure impact nationally and internationally. This document will evolve and be periodically reviewed in partnership with the Earth science education community.
CTAEMS MDP Optimal Planner is a problem-solving software designed to command a single spacecraft/rover, or a team of spacecraft/rovers, to perform the best action possible at all times according to an abstract model of the spacecraft/rover and its environment. It also may be useful in solving logistical problems encountered in commercial applications such as shipping and manufacturing. The planner reasons around uncertainty according to specified probabilities of outcomes using a plan hierarchy to avoid exploring certain kinds of suboptimal actions. Also, planned actions are calculated as the state-action space is expanded, rather than afterward, to reduce by an order of magnitude the processing time and memory used. The software solves planning problems with actions that can execute concurrently, that have uncertain duration and quality, and that have functional dependencies on others that affect quality. These problems are modeled in a hierarchical planning language called C_TAEMS, a derivative of the TAEMS language for specifying domains for the DARPA Coordinators program. In realistic environments, actions often have uncertain outcomes and can have complex relationships with other tasks. The planner approaches problems by considering all possible actions that may be taken from any state reachable from a given, initial state, and from within the constraints of a given task hierarchy that specifies what tasks may be performed by which team member.
A document describes a methodology for utilizing image data downlinked from cameras aboard a robotic ground vehicle (rover) on a remote planet for analyzing and planning operations of the vehicle and of any associated spacecraft. Traditionally, the cataloging and presentation of large numbers of downlinked planetary-exploration images have been done by use of two organizational methods: temporal organization and correlation between activity plans and images. In contrast, the present methodology involves spatial indexing of image data by use of the computational discipline of geographic information systems (GIS), which has been maturing in terrestrial applications for decades, but, until now, has not been widely used in support of exploration of remote planets. The use of GIS to catalog data products for analysis is intended to increase efficiency and effectiveness in planning rover operations, just as GIS has proven to be a source of powerful computational tools in such terrestrial endeavors as law enforcement, military strategic planning, surveying, political science, and epidemiology. The use of GIS also satisfies the need for a map-based user interface that is intuitive to rover-activity planners, many of whom are deeply familiar with maps and know how to use them effectively in field geology.
This presentation describes the process used to collect, review, integrate, and assess research requirements desired to be a part of research and payload activities conducted on the ISS. The presentation provides a description of: where the requirements originate, to whom they are submitted, how they are integrated into a requirements plan, and how that integrated plan is formulated and approved. It is hoped that from completing the review of this presentation, one will get an understanding of the planning process that formulates payload requirements into an integrated plan used for specifying research activities to take place on the ISS.
The Aerial Onboard Autonomous Science Investigation System (AerOASIS) system provides autonomous planning and execution capabilities for aerial vehicles (see figure). The system is capable of generating high-quality operations plans that integrate observation requests from ground planning teams, as well as opportunistic science events detected onboard the vehicle while respecting mission and resource constraints. AerOASIS allows an airborne planetary exploration vehicle to summarize and prioritize the most scientifically relevant data; identify and select high-value science sites for additional investigation; and dynamically plan, schedule, and monitor the various science activities being performed, even during extended communications blackout periods with Earth.
This paper discusses a suite of multi sector planning tools for trajectory-based operations that were developed and evaluated in the Airspace Operations Laboratory (AOL) at the NASA Ames Research Center. The toolset included tools for traffic load and complexity assessment as well as trajectory planning and coordination. The situation assessment tools included an integrated suite of interactive traffic displays, load tables, load graphs, and dynamic aircraft filters. The planning toolset allowed for single and multi aircraft trajectory planning and data communication-based coordination of trajectories between operators. Also newly introduced was a real-time computation of sector complexity into the toolset that operators could use in lieu of aircraft count to better estimate and manage sector workload, especially in situations with convective weather. The tools were used during a joint NASA/FAA multi sector planner simulation in the AOL in 2009 that had multiple objectives with the assessment of the effectiveness of the tools being one of them. Current air traffic control operators who were experienced as area supervisors and traffic management coordinators used the tools throughout the simulation and provided their usefulness and usability ratings in post simulation questionnaires. This paper presents these subjective assessments as well as the actual usage data that was collected during the simulation. The toolset was rated very useful and usable overall. Many elements received high scores by the operators and were used frequently and successfully. Other functions were not used at all, but various requests for new functions and capabilities were received that could be added to the toolset.
A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.
Autonomous vehicles require optimal path planning algorithms to achieve mission goals while avoiding obstacles and being robust to uncertainties. The uncertainties arise from exogenous disturbances, modeling errors, and sensor noise, which can be characterized via stochastic models. Previous work defined a notion of robustness in a stochastic setting by using the concept of chance constraints. This requires that mission constraint violation can occur with a probability less than a prescribed value.In this paper we describe a novel method for optimal chance constrained path planning with feedback design. The approach optimizes both the reference trajectory to be followed and the feedback controller used to reject uncertainty. Our method extends recent results in constrained control synthesis based on convex optimization to solve control problems with nonconvex constraints. This extension is essential for path planning problems, which inherently have nonconvex obstacle avoidance constraints. Unlike previous approaches to chance constrained path planning, the new approach optimizes the feedback gain as wellas the reference trajectory.The key idea is to couple a fast, nonconvex solver that does not take into account uncertainty, with existing robust approaches that apply only to convex feasible regions. By alternating between robust and nonrobust solutions, the new algorithm guarantees convergence to a global optimum. We apply the new method to an unmanned aircraft and show simulation results that demonstrate the efficacy of the approach.
A human-in-the-loop (HITL) simulation was conducted in May 2010 to determine the feasibility and value 01 conducting multi-sector planning (MSP) operations in a mixed equipage environment. Aircraft were categorized as equipped or unequipped based on the presence or absence of an air-ground data communications (Data Comm) capability for receiving auto-loadable clearances and transfer of communication messages from the air navigation service provider (ANSP). The purpose of the study was to determine the feasibility and possible benefits of introducing multi-sector planning in a mixed equipage context, or whether Data Comm equipage was required for MSP operations. Each test scenario presented one of three different equipage levels to the controllers (10%, 50% or 90% equipped aircraft), so that the operational impact of different equipage levels could be observed. Operational feasibility assessment addressed two related questions: (1) are MSP operations feasible for unequipped aircraft, and (2) are they feasible in a mixed equipage context. Similarly, two categories of potential benefits were explored: (1) system performance improvements (e.g., throughput, workload) associated with MSP at different equipage levels, and (2) the possibility of providing differential service for equipage through MSP operations. Tool requirements (for both planning and controller stations), as well as planning and coordination procedures - within facility (traffic management unit/operational area) and within sector (R-Side/D-Side) - were two other topics addressed in the study. Overall, results suggested that MSP operations were feasible in a mixed equipage environment and that the tools were effective with both equipped and unequipped aircraft. Using the MSP tools, traffic management coordinators were able to manage controller task load, effectively balancing throughput with complexity and controller task load at each of the three equipage levels tested.
In 2007 the Johnson Space Center s Mission Operations Directorate (MOD) management team challenged their organizations to find ways to reduce the cost of operations for supporting the International Space Station (ISS) in the Mission Control Center (MCC). Each MOD organization was asked to define and execute projects that would help them attain cost reductions by 2012. The MOD Operations Division Flight Planning Branch responded to this challenge by launching several software automation projects that would allow them to greatly improve console operations and reduce ISS console staffing and intern reduce operating costs. These tasks ranged from improving the management and integration mission plan changes, to automating the uploading and downloading of information to and from the ISS and the associated ground complex tasks that required multiple decision points. The software solutions leveraged several different technologies including customized web applications and implementation of industry standard web services architecture; as well as engaging a previously TRL 4-5 technology developed by Ames Research Center (ARC) that utilized an intelligent agent-based system to manage and automate file traffic flow, archive data, and generate console logs. These projects to date have allowed the MOD Operations organization to remove one full time (7 x 24 x 365) ISS console position in 2010; with the goal of eliminating a second full time ISS console support position by 2012. The team will also reduce one long range planning console position by 2014. When complete, these Flight Planning Branch projects will account for the elimination of 3 console positions and a reduction in staffing of 11 engineering personnel (EP) for ISS.
Topics in this presentation are: Constellation Ares I/Orion/Ground Ops Elements Orion Ground Operations Flow Orion Operations Planning Process and Toolset Overview, including: 1 Orion Concept of Operations by Phase 2 Ops Analysis Capabilities Overview 3 Operations Planning Evolution 4 Functional Flow Block Diagrams 5 Operations Timeline Development 6 Discrete Event Simulation (DES) Modeling 7 Ground Operations Planning Document Database (GOPDb) Using Operations Planning Tools for Operability Improvements includes: 1 Kaizen/Lean Events 2 Mockups 3 Human Factors Analysis