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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

A Technology Plan for Enabling Commercial Space Business

The National Aeronautics and Space Administration's (NASA) Advanced Space Transportation Program is a customer driven, focused technology program that supports the NASA Strategic Plan and considers future commercial space business projections. The initial cycle of the Advanced Space Transportation Program implementation planning was conducted from December 1995 through February 1996 and represented increased NASA emphasis on broad base technology development with the goal of dramatic reductions in the cost of space transportation. The second planning cycle, conducted in January and February 1997, updated the program implementation plan based on changes in the external environment, increased maturity of advanced concept studies, and current technology assessments. The program has taken a business-like approach to technology development with a balanced portfolio of near, medium, and long-term strategic targets. Strategic targets are influenced by Earth science, space science, and exploration objectives as well as commercial space markets. Commercial space markets include those that would be enhanced by lower cost transportation as well as potential markets resulting in major increases in space business induced by reductions in transportation cost. The program plan addresses earth-to-orbit space launch, earth orbit operations and deep space systems. It also addresses all critical transportation system elements; including structures, thermal protection systems, propulsion, avionics, and operations. As these technologies are matured, integrated technology flight experiments such as the X-33 and X-34 flight demonstrator programs support near-term (one to five years) development or operational decisions. The Advanced Space Transportation Program and the flight demonstrator programs combine business planning, ground-based technology demonstrations and flight demonstrations that will permit industry and NASA to commit to revolutionary new space transportation systems beginning at the turn of the century and continuing far into the future.

Lyles, Garry M.↗
NASA NTRS1994

Practical Planning in COLLAGE

COLLAGE is a domain-independent planner that differs from traditional planners in two key ways: (1) it uses a diverse and extendible set of (it action-based) plan constructions methods; and (2) it utilizes a technique called (it localization) to partition the planning problem into smaller (and potentially interacting) sub problems. In this paper, we describe these features and how they are exploited in two different real-world planning domains. The first domain, building construction planning, has served as a framework for us to investigate how localization can improve scalability. The second domain, data analysis planning, benefits from COLLAGE's unique plan construction and representation methods. In addition, we describe extensions that were necessary to tackle these real-world problems.

Lansky, Amy L.↗
NASA NTRS1995

TRACON Aircraft Arrival Planning and Optimization Through Spatial Constraint Satisfaction

A new aircraft arrival planning and optimization algorithm has been incorporated into the Final Approach Spacing Tool (FAST) in the Center-TRACON Automation System (CTAS) developed at NASA-Ames Research Center. FAST simulations have been conducted over three years involving full-proficiency, level five air traffic controllers from around the United States. From these simulations an algorithm, called Spatial Constraint Satisfaction, has been designed, coded, undergone testing, and soon will begin field evaluation at the Dallas-Fort Worth and Denver International airport facilities. The purpose of this new design is an attempt to show that the generation of efficient and conflict free aircraft arrival plans at the runway does not guarantee an operationally acceptable arrival plan upstream from the runway -information encompassing the entire arrival airspace must be used in order to create an acceptable aircraft arrival plan. This new design includes functions available previously but additionally includes necessary representations of controller preferences and workload, operationally required amounts of extra separation, and integrates aircraft conflict resolution. As a result, the Spatial Constraint Satisfaction algorithm produces an optimized aircraft arrival plan that is more acceptable in terms of arrival procedures and air traffic controller workload. This paper discusses the current Air Traffic Control arrival planning procedures, previous work in this field, the design of the Spatial Constraint Satisfaction algorithm, and the results of recent evaluations of the algorithm.

Bergh, Christopher P.↗
NASA NTRS2002

Planning Under Continuous Time and Resource Uncertainty: A Challenge for AI

There has been considerable work in Al on decision-theoretic planning and planning under uncertainty. Unfortunately, all of this work suffers from one or more of the following limitations: 1) it relies on very simple models of actions and time, 2) it assumes that uncertainty is manifested in discrete action outcomes, and 3) it is only practical for very small problems. For many real world problems, these assumptions fail to hold. A case in point is planning the activities for a Mars rover. For this domain none of the above assumptions are valid: 1) actions can be concurrent and have differing durations, 2) there is uncertainty concerning action durations and consumption of continuous resources like power, and 3) typical daily plans involve on the order of a hundred actions. We describe the rover problem, discuss previous work on planning under uncertainty, and present a detailed. but very small, example illustrating some of the difficulties of finding good plans.

Bresina, John↗
NASA NTRS2002

Contingency Planning for Planetary Rovers

There has been considerable work in AI on planning under uncertainty. But this work generally assumes an extremely simple model of action that does not consider continuous time and resources. These assumptions are not reasonable for a Mars rover, which must cope with uncertainty about the duration of tasks, the power required, the data storage necessary, along with its position and orientation. In this paper, we outline an approach to generating contingency plans when the sources of uncertainty involve continuous quantities such as time and resources. The approach involves first constructing a "seed" plan, and then incrementally adding contingent branches to this plan in order to improve utility. The challenge is to figure out the best places to insert contingency branches. This requires an estimate of how much utility could be gained by building a contingent branch at any given place in the seed plan. Computing this utility exactly is intractable, but we outline an approximation method that back propagates utility distributions through a graph structure similar to that of a plan graph.

Dearden, Richard↗
NASA NTRS2002

Strategic Plan

The purpose of this document is to present the strategic plan and associated organizational structure that the National Space Biomedical Research Institute (NSBRI) will utilize to achieve the defined mission and objectives provided by NASA. Much of the information regarding the background and establishment of the NSBRI by NASA has been provided in other documentation and will not be repeated in this Strategic Plan. This Strategic Plan is presented in two volumes. Volume I (this volume) begins with an Introduction (Section 2) that provides the Institute's NASA-defined mission and objectives, and the organizational structure adopted to implement these through three Strategic Programs: Countermeasure Research; Education, Training and Outreach; and Cooperative Research and Development. These programs are described in Sections 3 to 5. Each program is presented in a similar way, using four subsections: Goals and Objectives; Current Strategies; Gaps and Modifications; and Resource Requirements. Section 6 provides the administrative infrastructure and total budget required to implement the Strategic Programs and assures that they form a single cohesive plan. This plan will ensure continued success of the Institute for the next five years. Volume II of the Strategic Plan provides an in-depth analysis of the current and future strategic programs of the 12 current NSBRI teams, including their goals, objectives, mutual interactions and schedules.

Source record↗
NASA NTRS2001

A Constraint-based Attribute and Interval Planning

In this paper we introduce Constraint-based Attribute and Interval Planning (CAIP), a new paradigm for representing and reasoning about plans. The paradigm enables the description of planning domains with time, resources, concurrent activities, mutual exclusions among sets of activities, disjunctive preconditions and conditional effects. We provide a theoretical foundation for the paradigm using a mapping to first order logic. We also show that CAIP plans are naturally expressed by networks of constraints, and that planning maps directly to dynamic constraint reasoning. In addition, we show how constraint templates are used to provide a compact mechanism for describing planning domains.

Frank, Jeremy↗
NASA NTRS2002

Planning Systems for Distributed Operations

This viewgraph representation presents an overview of the mission planning process involving distributed operations (such as the International Space Station (ISS)) and the computer hardware and software systems needed to support such an effort. Topics considered include: evolution of distributed planning systems, ISS distributed planning, the Payload Planning System (PPS), future developments in distributed planning systems, Request Oriented Scheduling Engine (ROSE) and Next Generation distributed planning systems.

Maxwell, Theresa G.↗
NASA NTRS2003

Incremental Contingency Planning

There has been considerable work in AI on planning under uncertainty. However, this work generally assumes an extremely simple model of action that does not consider continuous time and resources. These assumptions are not reasonable for a Mars rover, which must cope with uncertainty about the duration of tasks, the energy required, the data storage necessary, and its current position and orientation. In this paper, we outline an approach to generating contingency plans when the sources of uncertainty involve continuous quantities such as time and resources. The approach involves first constructing a "seed" plan, and then incrementally adding contingent branches to this plan in order to improve utility. The challenge is to figure out the best places to insert contingency branches. This requires an estimate of how much utility could be gained by building a contingent branch at any given place in the seed plan. Computing this utility exactly is intractable, but we outline an approximation method that back propagates utility distributions through a graph structure similar to that of a plan graph.

Dearden, Richard↗
NASA NTRS2003

Optimal Limited Contingency Planning

For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications where it is desirable to strictly limit the number of decision points and branches in a plan. This raises the question of how one goes about finding optimal plans containing only a limited number of branches. In this paper, we present an any-time algorithm for optimal k-contingency planning. It is the first optimal algorithm for limited contingency planning that is not an explicit enumeration of possible contingent plans. By modelling the problem as a partially observable Markov decision process, it implements the Bellman optimality principle and prunes the solution space. We present experimental results of applying this algorithm to some simple test cases.

Meuleau, Nicolas↗
NASA NTRS2003

Choosing Objectives in Over-Subscription Planning

Many NASA planning problems are over-subscription problems - that is, there are a large number of possible goals of differing value, and the planning system must choose a subset &it car! be accomplished within the limited time and resources available. Examples include planning for telescopes like Hubble, SIRTF, and SOFIA; scheduling for the Deep Space Network; and planning science experiments for a Mars rover. Unfortunately, existing planning systems are not designed to deal with problems like this - they expect a well-defined conjunctive goal and terminate in failure unless the entire goal is achieved. In this paper we develop techniques for over-subscription problems that assist a classical planner in choosing which goals to achieve, and the order in which to achieve them. These techniques use plan graph cost-estimation techniques to construct an orienteering problem, which is then used to provide heuristic advice on the goals and goal order that should considered by a planner.

Smith, David E.↗
NASA NTRS2003

Path to a Research Plan

This viewgraph presentation discusses the status and goals for the NASA OBPR Physical Science Research Program. The following text was used to summarize the presentation. The OBPR Physical Sciences Research program has been comprehensively reviewed and endorsed by National Research Council. The value and need for the research have been re-affirmed. The research program has been prioritized and resource re-allocations have been carried out through an OBPR-wide process. An increasing emphasis on strategic, mission-oriented research is planned. The program will strive to maintain a balance between strategic and fundamental research. A feasible ISS flight research program fitting within the budgetary and ISS resource envelopes has been formulated for the near term (2003-2007). The current ISS research program will be significantly strengthened starting 2005 by using discipline dedicated research facility racks. A research re-planning effort has been initiated and will include active participation from the research community in the next few months. The research re-planning effort will poise PSR to increase ISS research utilization for a potential enhancement beyond ISS IP Core Complete. The Physical Sciences research program readily integrates the cross-disciplinary requirements of the NASA and OBPR strategic objectives. Each fundamental research thrust will develop a roadmap through technical workshops and Discipline Working Groups (DWGs). Most fundamental research thrusts will involve cross-disciplinary efforts. A Technology Roadmap will guide the Strategic Research for Exploration thrust. The Research Plan will integrate and coordinate fundamental Research Thrusts Roadmaps with the Technology Roadmap. The Technology Roadmap will be developed in coordination with other OBPR programs as well as other Enterprise (R,S,M,N). International Partners will contribute to the roadmaps and through research coordination. The research plan will be vetted with the discipline working groups, the BPRAC subcommittees, and with the BPRAC. Recommendations from NRC past and current committees will be implemented whenever appropriate.Proposed theme element content will be "missionized" around planned content and potential new projects (facilities, modules, initiatives) on approximately a five-year horizon, with the approval of PSRD management. Center/science working group teams will develop descriptions of "mission" objectives, value, and requirements. Purpose is to create a competitive environment for concept development and to stimulate community ownership/advocacy. Proposed theme elements reviewed and approved by PSRD management. Strawman roadmaps for themes developed. Program budget and technology requirements verified. Theme elements are prioritized with the input of advisory groups. Integration into program themes (questions) and required technology investments are defined by science and technology roadmaps. Review and assessment by OBPR management.

Chiaramonte, Fran↗
NASA NTRS2005

Technology Plan for the Terrestrial Planet Finder Interferometer

The technology plan for the Terrestrial Planet Finder Interferometer (TPF-I) describes the breadth of technology development currently envisaged to enable TPF-I to search for habitable worlds around nearby stars. TPF-I is currently in Pre-Phase A (the Advanced Study Phase) of its development. For planning purposes, it is expected to enter into Phase A in 2010 and be launched sometime before 2020. TPF-I is being developed concurrently with the Terrestrial Planet Finder Coronagraph (TPF-C), whose launch is anticipated in 201 6. The missions are being designed with the capability to detect Earth-like planets should they exist in the habitable zones of Sun-like (F,G, and K) stars out to a distance of about 60 light-years. Each mission will have the starlight-suppression and spectroscopic capability to enable the characterization of extrasolar planetary atmospheres, identifying biomarkers and signs of life. TPF-C is designed as a visible-light coronagraph; TPF-I is designed as a mid-infrared formation-flying interferometer. The two missions, working together, promise to yield unambiguous detections and characterizations of Earth-like planets. The challenges of planet detections with mid-infrared formation-flying interferometry are described within this technology plan. The approach to developing the technology is described through roadmaps that lead from our current state of the art through the different phases of mission development to launch. Technology metrics and milestones are given to measure progress. The emphasis of the plan is development and acquisition of technology during pre-Phase A to establish feasibility of the mission to enter Phase A sometime around 2010. Plans beyond 2010 are outlined. The plan contains descriptions of the development of new component technology as well as testbeds that demonstrate the viability of new techniques and technology required for the mission. Starlight-suppression (nulling) and formation-flying technology are highlighted. Although the techniques are described herein, the descriptions are only at a high-level, and tutorial material is not included. The reader is expected to have some familiarity with the principles of long-baseline mid-infrared interferometry. Selected references to existing literature are given where relevant.

Lawson, Peter R.↗
NASA NTRS2006

Plan Execution Interchange Language (PLEXIL)

Plan execution is a cornerstone of spacecraft operations, irrespective of whether the plans to be executed are generated on board the spacecraft or on the ground. Plan execution frameworks vary greatly, due to both different capabilities of the execution systems, and relations to associated decision-making frameworks. The latter dependency has made the reuse of execution and planning frameworks more difficult, and has all but precluded information sharing between different execution and decision-making systems. As a step in the direction of addressing some of these issues, a general plan execution language, called the Plan Execution Interchange Language (PLEXIL), is being developed. PLEXIL is capable of expressing concepts used by many high-level automated planners and hence provides an interface to multiple planners. PLEXIL includes a domain description that specifies command types, expansions, constraints, etc., as well as feedback to the higher-level decision-making capabilities. This document describes the grammar and semantics of PLEXIL. It includes a graphical depiction of this grammar and illustrative rover scenarios. It also outlines ongoing work on implementing a universal execution system, based on PLEXIL, using state-of-the-art rover functional interfaces and planners as test cases.

Estlin, Tara↗
NASA NTRS2005

Model Checking Artificial Intelligence Based Planners: Even the Best Laid Plans Must Be Verified

Automated planning systems (APS) are gaining acceptance for use on NASA missions as evidenced by APS flown On missions such as Orbiter and Deep Space 1 both of which were commanded by onboard planning systems. The planning system takes high level goals and expands them onboard into a detailed of action fiat the spacecraft executes. The system must be verified to ensure that the automatically generated plans achieve the goals as expected and do not generate actions that would harm the spacecraft or mission. These systems are typically tested using empirical methods. Formal methods, such as model checking, offer exhaustive or measurable test coverage which leads to much greater confidence in correctness. This paper describes a formal method based on the SPIN model checker. This method guarantees that possible plans meet certain desirable properties. We express the input model in Promela, the language of SPIN and express the properties of desirable plans formally.

model checking↗
NASA NTRS2008

Automated Data Assimilation and Flight Planning for Multi-Platform Observation Missions

This is a progress report on an effort in which our goal is to demonstrate the effectiveness of automated data mining and planning for the daily management of Earth Science missions. Currently, data mining and machine learning technologies are being used by scientists at research labs for validating Earth science models. However, few if any of these advanced techniques are currently being integrated into daily mission operations. Consequently, there are significant gaps in the knowledge that can be derived from the models and data that are used each day for guiding mission activities. The result can be sub-optimal observation plans, lack of useful data, and wasteful use of resources. Recent advances in data mining, machine learning, and planning make it feasible to migrate these technologies into the daily mission planning cycle. We describe the design of a closed loop system for data acquisition, processing, and flight planning that integrates the results of machine learning into the flight planning process.

Oza, Nikunj↗
NASA NTRS2007

Probabilistic Reasoning for Robustness in Automated Planning

A general-purpose computer program for planning the actions of a spacecraft or other complex system has been augmented by incorporating a subprogram that reasons about uncertainties in such continuous variables as times taken to perform tasks and amounts of resources to be consumed. This subprogram computes parametric probability distributions for time and resource variables on the basis of user-supplied models of actions and resources that they consume. The current system accepts bounded Gaussian distributions over action duration and resource use. The distributions are then combined during planning to determine the net probability distribution of each resource at any time point. In addition to a full combinatoric approach, several approximations for arriving at these combined distributions are available, including maximum-likelihood and pessimistic algorithms. Each such probability distribution can then be integrated to obtain a probability that execution of the plan under consideration would violate any constraints on the resource. The key idea is to use these probabilities of conflict to score potential plans and drive a search toward planning low-risk actions. An output plan provides a balance between the user s specified averseness to risk and other measures of optimality.

Schaffer, Steven↗
NASA NTRS2010

Tracking the Short Term Planning (STP) Development Process

Part of the National Aeronautics and Space Administration?s mission is to pioneer the future in space exploration, scientific discovery and aeronautics research is enhanced by discovering new scientific tools to improve life on earth. Sequentially, to successfully explore the unknown, there has to be a planning process that organizes certain events in the right priority. Therefore, the planning support team has to continually improve their processes so the ISS Mission Operations can operate smoothly and effectively. The planning support team consists of people in the Long Range Planning area that develop timelines that includes International Partner?s Preliminary STP inputs all the way through to publishing of the Final STP. Planning is a crucial part of the NASA community when it comes to planning the astronaut?s daily schedule in great detail. The STP Process is in need of improvement, because of the various tasks that are required to be broken down in order to get the overall objective of developing a Final STP done correctly. Then a new project came along in order to store various data in a more efficient database. "The SharePoint site is a Web site that provides a central storage and collaboration space for documents, information, and ideas."

Price, Melanie↗