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The major management systems used to plan and control NASA programs and resources are described as well as their integration to form the agency's general management approach in carrying out its mission. Documents containing more detailed descriptions of the processes and techniques involved in the agency's major management systems are listed.
A system for producing vehicle routes such as aircraft flight plans in the presence of weather and other hazards defines static and moving hazards with polygons drawn on a display containing graphic hazard regions. Different hazard types and intensities are displayed differently. Both lateral and vertical geographic depictions are displayed, and hazards can be displayed temporally as well. Users input information and thresholds for hazards.
Current NASA plans for lunar exploration include a human lunar landing system, comprised of separate descent andascent modules, with the eventual goal of reusability. Different oxygen production processes were studied to evaluatethe feasibility of producing 10 tons of oxygen per year assuming a high latitude landing location. The study includesconsideration of packaging the ISRU components on the descent module, methods to transfer the regolith from theexcavators to the processing plant which may be mounted well above the lunar surface, and general concept ofoperations for excavation, oxygen production, and liquefaction and storage. A solar-based power system was alsodesigned and packaged on the lander, including the use of direct solar thermal energy where appropriate.
The allocation of scarce spacecraft resources to multiple users has always been a difficult process. This difficulty arises from the fact that there are never enough resources to meet the stated requirements of the scientific investigators who compete to acquire their desired data sets.
Computer Resources International (CRI) has many years of experience in developing space planning and scheduling systems for the European Space Agency. Activities range from AIT/AIV planning over mission planning to research in on-board autonomy using advanced planning and scheduling technologies in conjunction with model based diagnostics. This article presents four projects carried out for ESA by CRI with various subcontractors: (1) DI, Distributed Intelligence for Ground/Space Systems is an on-going research project; (2) GMPT, Generic Mission Planning Toolset, a feasibility study concluded in 1993; (3) OPTIMUM-AIV, Open Planning Tool for AIV, development of a knowledge based AIV planning and scheduling tool ended in 1992; and (4) PlanERS-1, development of an AI and knowledge-based mission planning prototype for the ERS-1 earth observation spacecraft ended in 1991.
The Kansas City Division of Allied Signal Inc., as part of the Integrated Flexible Manufacturing Program (IFMP), is developing an integrated manufacturing environment. Several systems are being developed to produce standards and automation tools for specific activities within the manufacturing environment. The Advanced Manufacturing Development System (AMDS) is concentrating on information standards (STEP) and product data transfer; the Expert Cut Planner system (XCUT) is concentrating on machining operation process planning standards and automation capabilities; the Advanced Numerical Control system (ANC) is concentrating on NC data preparation standards and NC data generation tools; the Inspection Planning and Programming Expert system (IPPEX) is concentrating on inspection process planning, coordinate measuring machine (CMM) inspection standards and CMM part program generation tools; and the Intelligent Scheduling and Planning System (ISAPS) is concentrating on planning and scheduling tools for a flexible manufacturing system environment. All of these projects are working together to address information exchange, standardization, and information sharing to support rapid prototyping in a Flexible Manufacturing System (FMS) environment.
The African real time environmental monitoring using imaging satellites (Artemis) system, which should monitor precipitation and vegetation conditions on a continental scale, is presented. The hardware and software characteristics of the system are illustrated and the Artemis databases are outlined. Plans for the system include the use of hourly digital Meteosat data and daily NOAA/AVHRR data to study environmental conditions. Planned mapping activities include monthly rainfall anomaly maps, normalized difference vegetation index maps for ten day and monthly periods with a spatial resolution of 7.6 km, ten day crop/rangeland moisture availability maps, and desert locust potential breeding activity factor maps for a plague prevention program.
The functions are identified and described in chart form as a tree in which the basic functions, to 'Provide National Identification Service,' are shown at the top. The lower levels of the tree branch out to indicate functions and sub-functions. Symbols are used to indicate whether or not a function was automated in the AIDS 1 or 2 system or is planned to be automated in the AIDS 3 system. The tree chart is shown in detail.
In manned space operations today, the astronauts' activity schedules are preplanned and adjusted daily on Earth. We have developed the Distributed Collaboration and Interaction (DCI) multi-agent system to investigate automating aspects of human activity management. The DCI System assists (1) plan generation, (2) human activity tracking, (3) plan revision, and (4) mixed initiative interaction with the plan. We have deployed and evaluated the DCI system at JSC to assist control engineers in managing anomaly handling activities for automated life support systems. DCI operated round the clock for 20 months in the Water Research Facility at JSC. Using this software, we reduced anomaly response time by engineers from up to 10 hours in previous tests to under an hour. Based on this evaluation, we conclude that agent assistance for schedule management has potential to improve astronaut activity awareness and reduce response time in situations where crew are interrupted to handle anomalies.
Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 2040–2069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between −9% and −39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems.
Engineers and scientists often rely on their intuition and experience when designing soft robotic systems. The development of performant controllers and motion plans for these systems commonly requires time-consuming iterations on hardware. We present the SoMo (Soft Motion) toolkit, a software framework that makes it easy to instantiate and control typical continuum manipulators in an accurate physics simulator. SoMo introduces a standardized and human-readable description format for continuum manipulators. It leverages this description format and the Bullet physics engine to enable fast and accurate simulations of soft and soft-rigid hybrid robots in environments with complex contact interactions. This allows users to vary design and control parameters across simulations with minimal effort. We compare the capabilities of SoMo to other physics simulators and highlight the benefits and accuracy of SoMo by demonstrating the agreement between simulation and real-world experiments on several examples; these include an in-hand manipulation task with continuum fingers, an automated exploration of how to design soft fingers for precision grasping, and a brief snake locomotion study. Overall, SoMo provides an accessible way for designers of soft robotic hardware and control systems to gain access to a simulation-accelerated workflow.
Slide presentation for Vertiport Automation System (VAS) Software breakout session introducing the planning and pre-flight phase.
Technology development for upper atmospheric sounding system
The sensitivity of the National Photovoltaic Research Program goals to changes in individual photovoltaic system parameters is explored. Using the relationship between lifetime cost and system performance parameters, tests were made to see how overall photovoltaic system energy costs are affected by changes in the goals set for module cost and efficiency, system component costs and efficiencies, operation and maintenance costs, and indirect costs. The results are presented in tables and figures for easy reference.
In this paper, we discuss our approach to making the behavior of planetary rovers more robust for the purpose of increased productivity. Due to the inherent uncertainty in rover exploration, the traditional approach to rover control is conservative, limiting the autonomous operation of the rover and sacrificing performance for safety. Our objective is to increase the science productivity possible within a single uplink by allowing the rover's behavior to be specified with flexible, contingent plans and by employing dynamic plan adaptation during execution. We have deployed a system exhibiting flexible, contingent execution; this paper concentrates on our ongoing efforts on plan adaptation, Plans can be revised in two ways: plan steps may be deleted, with execution continuing with the plan suffix; and the current plan may be merged with an "alternate plan" from an on-board library. The plan revision action is chosen to maximize the expected utility of the plan. Plan merging and action deletion constitute a more conservative general-purpose planning system; in return, our approach is more efficient and more easily verified, two important criteria for deployed rovers.
The installation of the Centralized Storm Information System (CSIS) at the NOAA operational complex in Kansas City, Missouri is described. This complex includes the National Severe Storms Forecast center and a Satellite Field Service Station which is denoted in this research plan as NSSFC. CSIS computers will act in concert to merge analyze the many data sets needed to forecast severe convective storms. Specific aspects of CSIS are evaluated against the CSIS objectives. The functions to be evaluated characterize the attributes of a generalized interactive computer system. A major development in the CSIS program will allow communication between CSIS and the NSSFC Eclipse computer.
Recommendations for logistics activities and logistics planning are presented based on the assumption that a system prime contractor will perform logistics functions to support all program hardware and will implement a logistics system to include the planning and provision of products and services to assure cost effective coverage of the following: maintainability; maintenance; spares and supply support; fuels; pressurants and fluids; operations and maintenance documentation training; preservation, packaging and packing; transportation and handling; storage; and logistics management information reporting. The training courses, manpower, materials, and training aids required will be identified and implemented in a training program.
The planning problem has traditionally been treated separately from the scheduling problem. However, as more realistic domains are tackled, it becomes evident that the problem of deciding on an ordered set of tasks to achieve a set of goals cannot be treated independently of the problem of actually allocating resources to the tasks. Doing so would result in losing the robustness and flexibility needed to deal with imperfectly modeled domains. Completable scheduling is an approach which integrates the two problems by allowing an a priori planning module to defer particular planning decisions, and consequently the associated scheduling decisions, until execution time. This allows a completable scheduling system to maximize plan flexibility by allowing runtime information to be taken into consideration when making planning and scheduling decision. Furthermore, through the criteria of achievability placed on deferred decision, a completable scheduling system is able to retain much of the goal-directedness and guarantees of achievement afforded by a priori planning. The completable scheduling approach is further enhanced by the use of contingent explanation-based learning, which enables a completable scheduling system to learn general completable plans from example and improve its performance through experience. Initial experimental results show that completable scheduling outperforms classical scheduling as well as pure reactive scheduling in a simple scheduling domain.