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At least 19 records

MSL relay coordination and tactical planning in the era of InSight, MAVEN, and TGO

This study examines an approach for optimizing the scheduling of regular relay communications between the Mars Science Laboratory (MSL) rover and the non-sun-synchronous Mars orbiters MAVEN and TGO as well as the impacts of the approaching InSight landing on MSL relay and tactical planning. Rover operations require knowledge of recently executed activities, termed decisional data, in order to inform tactical activity planning. As a result, timely and routine data return is critical for nominal rover operations. Mars orbiters are used as relay assets to achieve such timeliness.

Thomas, Steven↗

Integrating tactical planning, operational planning and scheduling using data-driven feasibility analysis

Supply chain operations and scheduling are well-studied problems in the literature. Although these problems are related, they are often solved sequentially. This uncoordinated approach usually leads to sub-optimal solutions. Here this paper proposes a methodology for integrating scheduling operations into the supply chain network, motivated by the available enterprise data, and feasibility analysis. Existing literature on integrated models for addressing the supply chain is reviewed and classified. Then the mathematical model formulation for each level is discussed, after which the proposed data-driven integrated framework is described. The methodology is tested on two different case studies of varying dimensions. For each case study, the solution solves a multi-objective problem with the overall aim of an optimal solution that is robust towards achieving optimal cost while keeping customer satisfaction in mind.

42 ENGINEERING↗

NASA’s Four-Layer Cake: Systematic Approach for Developing a Digital Transformation Tactical Plan for Organizations

With the current industry movement to “digitally transform” there is much fervor to do something, to change in some way, to do things differently and digitally; however, the last decade has shown that most organizations do not know where to start or abandon transformation efforts. And often the approaches taken fall in the realm of “low-hanging fruit” or “easy wins” which rarely result in the foundational change needed. NASA was no different in the early years of its digital transformation and this drove the development of what eventually became known as the “Four-Layer Cake”. The Four-Layer Cake provides the critical approach for determining the core areas for investment to gain the greatest return without having to boil the ocean or hope that the low-hanging fruit will provide the foundational elements for a domain’s transformation.

Digital engineering↗

Advanced Technologies for Future Spacecraft Cockpits and Space-based Control Centers

The National Aeronautics and Space Administration (NASA) is embarking on a new era of Space Exploration, aimed at sending crewed spacecraft beyond Low Earth Orbit (LEO), in medium and long duration missions to the Lunar surface, Mars and beyond. The challenges of such missions are significant and will require new technologies and paradigms in vehicle design and mission operations. Current roles and responsibilities of spacecraft systems, crew and the flight control team, for example, may not be sustainable when real-time support is not assured due to distance-induced communication lags, radio blackouts, equipment failures, or other unexpected factors. Therefore, technologies and applications that enable greater Systems and Mission Management capabilities on-board the space-based system will be necessary to reduce the dependency on real-time critical Earth-based support. The focus of this paper is in such technologies that will be required to bring advance Systems and Mission Management capabilities to space-based environments where the crew will be required to manage both the systems performance and mission execution without dependence on the ground. We refer to this concept as autonomy. Environments that require high levels of autonomy include the cockpits of future spacecraft such as the Mars Exploration Vehicle, and space-based control centers such as a Lunar Base Command and Control Center. Furthermore, this paper will evaluate the requirements, available technology, and roadmap to enable full operational implementation of onboard System Health Management, Mission Planning/re-planning, Autonomous Task/Command Execution, and Human Computer Interface applications. The technology topics covered by the paper include enabling technology to perform Intelligent Caution and Warning, where the systems provides directly actionable data for human understanding and response to failures, task automation applications that automate nominal and Off-nominal task execution based on human input or integrated health state-derived conditions. Shifting from Systems to Mission Management functions, we discuss the role of automated planning applications (tactical planning) on-board, which receive data from the other cockpit automation systems and evaluate the mission plan against the dynamic systems and mission states and events, to provide the crew with capabilities that enable them to understand, change, and manage the timeline of their mission. Lastly, we discuss the role of advanced human interface technologies that organize and provide the system md mission information to the crew in ways that maximize their situational awareness and ability to provide oversight and control of aLl the automated data and functions.

Garcia-Galan, Carlos↗

Challenging the Future - Journey to Excellence. Aeropropulsion strategic plan for the 1990's

Over the past several months, the Lewis Aeropropulsion Management Council (AMC) has conducted a critical assessment of its strategic plan. This assessment clearly indicated a need for change, both in the aeropropulsion program emphasis and in the approach to carrying out that program. Customers sent a strong message that the program must improve the timeliness of research and technology products and services and must work more closely with them to develop and transfer new technology. The strategic plan defines AMC's vision for the future and underlying organizational values. It contains a set of broad strategies and actions that point the way toward achieving the goals of customer satisfaction, organizational effectiveness, and programmatic excellence. Those strategies are expected to form the basis for the development of specific tactical plans by Lewis aeropropulsion thrust teams, divisions, and branches. To guide tactical planning of the aeropropulsion program, this strategic plan outlines the agency's strategic directions and long-range aeronautics goals, the aeropropulsion goals and key objectives for achieving them, projections of Lewis aeropropulsion budgets, planned allocations of resources, and the processes that will be used to measure success in carrying out the strategic plan.

Source record↗

A Comparison of Declarative and Hybrid Declarative-Procedural Models for Rover Operations

The MAPGEN [2] (Mixed-initiative Activity Plan GENerator) planning system is a great example of a hybrid procedural/declarative system where the advantages of each are leveraged to produce an effective planner/scheduler for Mars Exploration Rover tactical planning. We explore the adaptation of the same domain to an entirely declarative planning system (ASPEN [4] Activity Scheduling and Planning ENvironment), and demonstrate that, with some translation, much of the procedural knowledge encoding is amenable to a declarative knowledge encoding.

declarative domain representations↗

Concept of Operations for OSIRIS-REx Optical Navigation Image Planning

Optical navigation (OpNav) is a critical subsystem of the OSIRIS-REx asteroid sample return mission, which operated in the vicinity of near-Earth asteroid (101955) Bennu from August 2018 through April 2021. A substantial amount of mission resources across multiple subsystems and institutions is required to ensure that the OpNav data are successfully acquired. The KinetX OpNav team, part of the Flight Dynamics System (FDS), is responsible for performing required analysis to develop the OpNav operations plans; requesting, reviewing and verifying the plans; and ultimately using the image data for critical navigation operations. The FDS team, responsible for the mission navigation, is operated by KinetX Aerospace with management and operations support from NASA’s Goddard Space Flight Center. The Science Processing and Operations Center (SPOC), located at the University of Arizona’s Lunar and Planetary Laboratory, is responsible for generating the planning products for all science and most OpNav data. These plans are integrated into the spacecraft sequences, tested, and commanded by the Mission Support Area (MSA) at Lockheed Martin Space. To ensure mission-critical navigation image data are successfully acquired, the plan is developed through a waterfall of planning cycles over the course of 3 months prior to onboard plan execution. During the initial strategic planning for a mission phase, detailed analysis is performed by the OpNav team to conceptualize the concept of operations (ConOps) for image data collection. This phase OpNav Narrative is included along with other strategic planning documents for the key ground segment stakeholders to review and provide feedback. The detailed OpNav plans get defined in the tactical planning cycle, which spans 8 to 3 weeks before the week-long integrated sequence is executed on-board the spacecraft. During the tactical cycle, the initial OpNav Request is submitted along with the science requests, kicking off development of the science and OpNav plans. Once the initial plan is drafted, interfaces are exercised so that the plan can be reviewed and iterated, if necessary. A rigorous schedule is followed by the planning teams during the implementation cycle, spanning the last 18 days before uplink, to ensure all the necessary integration, testing, and reviewing can occur on time. The development of the OpNav planning ConOps, including responsibilities, interfaces, timelines, and procedures, took extensive collaboration across mission elements and institutions. The process was robust throughout the 137 weeks of continuous Optical Navigation Operations at Bennu, which concluded on April 9th, 2021.

Coralie D. Adam↗

Human Research Program Integrated Research Plan

The Integrated Research Plan (IRP) describes the portfolio of Human Research Program (HRP) research and technology tasks. The IRP is the HRP strategic and tactical plan for research necessary to meet HRP requirements. The need to produce an IRP is established in HRP-47052, Human Research Program - Program Plan, and is under configuration management control of the Human Research Program Control Board (HRPCB). Crew health and performance is critical to successful human exploration beyond low Earth orbit. The Human Research Program (HRP) is essential to enabling extended periods of space exploration because it provides knowledge and tools to mitigate risks to human health and performance. Risks include physiological and behavioral effects from radiation and hypogravity environments, as well as unique challenges in medical support, human factors, and behavioral or psychological factors. The Human Research Program (HRP) delivers human health and performance countermeasures, knowledge, technologies and tools to enable safe, reliable, and productive human space exploration. Without HRP results, NASA will face unknown and unacceptable risks for mission success and post-mission crew health. This Integrated Research Plan (IRP) describes HRP s approach and research activities that are intended to address the needs of human space exploration and serve HRP customers and how they are integrated to provide a risk mitigation tool. The scope of the IRP is limited to the activities that can be conducted with the resources available to the HRP; it does not contain activities that would be performed if additional resources were available. The timescale of human space exploration is envisioned to take many decades. The IRP illustrates the program s research plan through the timescale of early lunar missions of extended duration.

Source record↗

Translating MAPGEN to ASPEN for MER

This software translates MAPGEN (Europa and APGEN) domains to ASPEN, and the resulting domain can be used to perform planning for the Mars Exploration Rover (MER). In other words, this is a conversion of two distinct planning languages (both declarative and procedural) to a third (declarative) planning language in order to solve the problem of faithful translation from mixed-domain representations into the ASPEN Modeling Language. The MAPGEN planning system is an example of a hybrid procedural/declarative system where the advantages of each are leveraged to produce an effective planner/scheduler for MER tactical planning. The adaptation of the planning system (ASPEN) was investigated, and, with some translation, much of the procedural knowledge encoding is amenable to declarative knowledge encoding. The approach was to compose translators from the core languages used for adapting MAGPEN, which consists of Europa and APGEN. Europa is a constraint- based planner/scheduler where domains are encoded using a declarative model. APGEN is also constraint-based, in that it tracks constraints on resources and states and other variables. Domains are encoded in both constraints and code snippets that execute according to a forward sweep through the plan. Europa and APGEN communicate to each other using proxy activities in APGEN that represent constraints and/or tokens in Europa. The composition of a translator from Europa to ASPEN was fairly straightforward, as ASPEN is also a declarative planning system, and the specific uses of Europa for the MER domain matched ASPEN s native encoding fairly closely. On the other hand, translating from APGEN to ASPEN was considerably more involved. On the surface, the types of activities and resources one encodes in APGEN appear to match oneto- one to the activities, state variables, and resources in ASPEN. But, when looking into the definitions of how resources are profiled and activities are expanded, one sees code snippets that access various information available during planning for the moment in time being planned to decide at the time what the appropriate profile or expansion is. APGEN is actually a forward (in time) sweeping discrete event simulator, where the model is composed of code snippets that are artfully interleaved by the engine to produce a plan/schedule. To solve this problem, representative code is simulated as a declarative series of task expansions. Predominantly, three types of procedural models were translated: loops, if statements, and code blocks. Loops and if statements were handled using controlled task expansion, and code blocks were handled using constraint networks that maintained the generation of results based on what the order of execution would be for a procedural representation. One advantage with respect to performance for MAPGEN is the use of APGEN s GUI. This GUI is written in C++ and Motif, and performs very well for large plans.

Rabideau, Gregg R.↗

Software reuse in spacecraft planning and scheduling systems

The use of a software toolkit and development methodology that supports software reuse is described. The toolkit includes source-code-level library modules and stand-alone tools which support such tasks as data reformatting and report generation, simple relational database applications, user interfaces, tactical planning, strategic planning and documentation. The current toolkit is written in C and supports applications that run on IBM-PC's under DOS and UNlX-based workstations under OpenLook and Motif. The toolkit is fully integrated for building scheduling systems that reuse AI knowledge base technology. A typical scheduling scenario and three examples of applications that utilize the reuse toolkit will be briefly described. In addition to the tools themselves, a description of the software evolution and reuse methodology that was used is presented.

Mclean, David↗

Balancing Predictive and Reactive Science Planning for Mars 2020 Perseverance

The design of the science planning process for a space science mission needs to find a balance between operational and resource constraints and scientific decision-making. Science planning has previously been characterized as either predictive or reactive. Predictive science planning is needed when constraints drive science activities to be planned far in advance. For example, a combination of long one-way light time plus high-stakes science decisions drove the Cassini-Huygens mission to Saturn to have an extremely predictive planning process. On the other extreme, reactive science planning is needed when constraints drive science activities to be planned based on the results of the previous plan. For example, the Mars Exploration Rover mission interacted with the surface of Mars, and so the planning team needed to know the state of the rover at the end of each planning cycle before starting the next cycle. Operational and resource constraints that require management on intermediate timescales has led to the development of a science planning process between these two extremes. For example, the Mars Science Laboratory is a technically complex rover and has a parallel predictive process that allows the operations team to manage engineering constraints several days in advance while maintaining the reactive tactical planning process similar to that of MER. The Mars 2020 Perseverance rover is a technically complex rover in the MSL style, but has an added layer of science complexity: it is tasked with collecting a returnable cache of scientifically valuable samples of Mars within prime mission. Thus, the science planning process also needs to accommodate high-stakes longer-term science decisions in the style of Cassini. In order to balance the push-pull of these constraints, we have developed a science campaign-focused operational paradigm for Mars 2020 Perseverance that allows for both predictive planning to accommodate technological complexity and high-stakes science decisions as well as reactive planning to accommodate the realities of interacting with the martian surface. This paradigm influenced the design of operational processes and operational tools.

Spanovich, Nicole↗

Partner with a Third-Party Delivery Service or Not? A Prediction-and-Decision Tool for Restaurants Facing Takeout Demand Surges During a Pandemic

Amidst the COVID-19 pandemic, restaurants become more reliant on no-contact pick-up or delivery ways for serving customers. As a result, they need to make tactical planning decisions such as whether to partner with online platforms, to form their own delivery team, or both. In this paper, we develop an integrated prediction-decision model to analyze the profit of combining the two approaches and to decide the needed number of drivers under stochastic demand. We first use the susceptible-infected-recovered (SIR) model to forecast future infected cases in a given region and then construct an autoregressive-moving-average (ARMA) regression model to predict food-ordering demand. Using predicted demand samples, we formulate a stochastic integer program to optimize food delivery plans. We conduct numerical studies using COVID-19 data and food-ordering demand data collected from local restaurants in Nuevo Leon, Mexico, from April to October 2020, to show results for helping restaurants build contingency plans under rapid market changes. Our method can be used under unexpected demand surges, various infection/vaccination status, and demand patterns. Here, our results show that a restaurant can benefit from partnering with third-party delivery platforms when (i) the subscription fee is low, (ii) customers can flexibly decide whether to order from platforms or from restaurants directly, (iii) customers require more efficient delivery, (iv) average delivery distance is long, or (v) demand variance is high.

97 MATHEMATICS AND COMPUTING↗

Applications of artificial intelligence to rotorcraft

The application of AI technology may have significant potential payoff for rotorcraft. In the near term, the status of the technology will limit its applicability to decision aids rather than total automation. The specific application areas are categorized into onboard and nonflight aids. The onboard applications include: fault monitoring, diagnosis, and reconfiguration; mission and tactics planning; situation assessment; navigation aids, especially in nap-of-the-earth flight; and adaptive man-machine interfaces. The nonflight applications include training and maintenance diagnostics.

Abbott, Kathy H.↗

Evaluation of Perspective and Coplanar Cockpit Displays of Traffic Information to Support Hazard Awareness in Free Flight

We examined the cockpit display representation of traffic, to support the pilot in tactical planning and conflict avoidance. Such displays may support the "free flight" concept, but can also support greater situation awareness in a non-free flight environment. Two perspective views and a coplanar display were contrasted in scenarios in which pilots needed to navigate around conflicting traffic, either in the absence (low workload) or presence (high workload) of a second intruder aircraft. All three formats were configured with predictive aiding vectors that explicitly represented the predicted point of closest pass, and predicted penetration of an alert zone around ownship. Ten pilots were assigned to each of the display conditions, and each flew a series of 60 conflict maneuvers that varied in their workload and the complexity of the conflict geometry. Results indicated a tendency to choose vertical over lateral maneuvers, a tendency which was amplified with the coplanar display. Vertical maneuvers by the intruder produced an added source of workload. Importantly, the coplanar display supported performance in all measures that was equal to or greater than either of the perspective displays (i.e., fewer predicted and actual conflicts, less extreme maneuvers). Previous studies that have indicated perspective superiority have only contrasted these with UNIplanar displays rather than the coplanar display used here.

Merwin, David H.↗

Inductive Learning Approaches for Improving Pilot Awareness of Aircraft Faults

Neural network flight controllers are able to accommodate a variety of aircraft control surface faults without detectable degradation of aircraft handling qualities. Under some faults, however, the effective flight envelope is reduced; this can lead to unexpected behavior if a pilot performs an action that exceeds the remaining control authority of the damaged aircraft. The goal of our work is to increase the pilot s situational awareness by informing him of the type of damage and resulting reduction in flight envelope. Our methodology integrates two inductive learning systems with novel visualization techniques. One learning system, the Inductive Monitoring System (IMS), learns to detect when a simulation includes faulty controls, while two others, Inductive Classification System (INCLASS) and multiple binary decision tree system (utilizing C4.5), determine the type of fault. In off-line training using only non-failure data, IMS constructs a characterization of nominal flight control performance based on control signals issued by the neural net flight controller. This characterization can be used to determine the degree of control augmentation required in the pitch, roll, and yaw command channels to counteract control surface failures. This derived information is typically sufficient to distinguish between the various control surface failures and is used to train both INCLASS and C4.5. Using data from failed control surface flight simulations, INCLASS and C4.5 independently discover and amplify features in IMS results that can be used to differentiate each distinct control surface failure situation. In real-time flight simulations, distinguishing features learned during training are used to classify control surface failures. Knowledge about the type of failure can be used by an additional automated system to alter its approach for planning tactical and strategic maneuvers. The knowledge can also be used directly to increase the pilot s situational awareness and inform manual maneuver decisions. Our multi-modal display of this information provides speech output to issue control surface failure warnings to a lesser-used communication channel and provides graphical displays with pilot-selectable !eve!s of details to issues additional information about the failure. We also describe a potential presentation for flight envelope reduction that can be viewed separately or integrated with an existing attitude indicator instrument. Preliminary results suggest that the inductive approach is capable of detecting that a control surface has failed and determining the type of fault. Furthermore, preliminary evaluations suggest that the interface discloses a concise summary of this information to the pilot.

Spikovska, Lilly↗

Research on International Space Station - Building a Partnership for the Future

As its name implies, the International Space Station is a platform where the research programs of 16 partner nations are conducted. While each partner pursues its own research priorities, cooperation and coordination of the various national and agency research programs occurs at multiple levels, from strategic through tactical planning to experiment operations. Since 2000, a significant number of experiments have been carried out in the Russian ISS utilization program, which consists of the Russian national program of fundamental and applied research in 11 research areas and international cooperative programs and contract activities. The US research program began with simple payloads in 2000 and was significantly expanded with the addition of the US Laboratory module Destiny in 2001, and its outfitting with seven research racks to date. The Canadian Space Agency (CSA), the European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) have made use of international cooperative arrangements with both the US and Russia to implement a variety of investigations in diverse research areas, and in the case of ESA included the flights of crewmembers to ISS as part of Soyuz Science Missions. In the future, ESA and JAXA will add their own research modules, Columbus and Kibo, respectively, to expand research capabilities both inside and outside ISS. In the aftermath of the Columbia accident and the temporary grounding of the Space Shuttle fleet, all ISS logistics have relied on Russian Progress and Sopz vehicles. The Russian national program has continued as before the Shuttle accident, as have international cooperative programs and contract activities, both during long-duration expeditions and visiting taxi missions. In several instances, Russian international cooperative activities with JAXA and ESA have also involved the use of US facilities and crewmembers in successful truly multilateral efforts. The US research program was rapidly refocused after the Shuttle accident to rely on greatly reduced upmass, and for the first time in the ISS program, US research hardware was launched on Progress vehicles and returned with crews on Soyuz spacecraft. It is hoped that these small but significant steps in international cooperation will lead to even greater endeavors once the remaining research modules are added to ISS.

Gindl, Heinz↗

Remote image analysis for Mars Exploration Rover mobility and manipulation operations

NASA's Mars Exploration Rovers are two sixwheeled, 175-kg robotic vehicles which have operated on Mars for over a year as of March 2005. The rovers are controlled by teams who must understand the rover's surroundings and develop command sequences on a daily basis. The tight tactical planning timeline and everchanging environment call for tools that allow quick assessment of potential manipulator targets and traverse goals, since command sequences must be developed in a matter of hours after receipt of new data from the rovers. Reachability maps give a visual indication of which targets are reachable by each rover's manipulator, while slope and solar energy maps show the rover operator which terrain areas are safe and unsafe from different standpoints.

image understanding↗