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Integrating planning and reactive control

Our research is developing persistent agents that can achieve complex tasks in dynamic and uncertain environments. We refer to such agents as taskable, reactive agents. An agent of this type requires a number of capabilities. The ability to execute complex tasks necessitates the use of strategic plans for accomplishing tasks; hence, the agent must be able to synthesize new plans at run time. The dynamic nature of the environment requires that the agent be able to deal with unpredictable changes in its world. As such, agents must be able to react to unanticipated events by taking appropriate actions in a timely manner, while continuing activities that support current goals. The unpredictability of the world could lead to failure of plans generated for individual tasks. Agents must have the ability to recover from failures by adapting their activities to the new situation, or replanning if the world changes sufficiently. Finally, the agent should be able to perform in the face of uncertainty. The Cypress system, described here, provides a framework for creating taskable, reactive agents. Several features distinguish our approach: (1) the generation and execution of complex plans with parallel actions; (2) the integration of goal-driven and event driven activities during execution; (3) the use of evidential reasoning for dealing with uncertainty; and (4) the use of replanning to handle run-time execution problems. Our model for a taskable, reactive agent has two main intelligent components, an executor and a planner. The two components share a library of possible actions that the system can take. The library encompasses a full range of action representations, including plans, planning operators, and executable procedures such as predefined standard operating procedures (SOP's). These three classes of actions span multiple levels of abstraction.

Wilkins, David E.↗

SEDAC information gateway plan V(1)

This annual update of the Information Gateway Plan incorporates changes recommended by the Socioeconomic Data and Applications Center (SEDAC) User Working Group (UWG) and reflects comments and suggestions from users, collaborators, and the Contracting Officer Technical Representative (COTR). The Information Gateway Plan is a concise and specific plan that outlines SEDAC activities and services in support of the earth and social sciences and other user communities. The SEDAC Information Gateway effort is a primary means by which the Earth Observing System Data and Information System (EOSDIS) can link meaningfully with a broad range of social science data sources and users in ways that lead to tangible benefits to the American people. The SEDAC Information Gateway provides interdisciplinary access to socioeconomic and physical science data and information resources held by SEDAC and numerous other institutions and networks around the world. The Plan describes the areas of research of earth scientists and socioeconomic scientists where interchange of data and information is most needed. It sets guidelines for the continued development of SEDAC's directory of social science datasets and establishes priorities for efforts to make data held by SEDAC or accessible through SEDAC available to the user community. The Plan also describes the means by which the SEDAC user community can access information products specified by the SEDAC Data and Applications Development Plan (DADP). Among other major activities, SEDAC will continue to enhance and operate a directory capability, interoperable with the Global Change Master Directory, that provides the socioeconomic community with information about earth science products and the earth science research community with information about socioeconomic data. The Information Gateway also serves as a unique and powerful access pathway for a wide range of users and potential users of socioeconomic and earth science data, including especially remote sensing data.

Chen, Robert S.↗

An Intelligent Crop Planning Tool for Controlled Ecological Life Support Systems

This paper describes a crop planning tool developed for the Controlled Ecological Life Support Systems (CELSS) project which is in the research phases at various NASA facilities. The Crop Planning Tool was developed to assist in the understanding of the long term applications of a CELSS environment. The tool consists of a crop schedule generator as well as a crop schedule simulator. The importance of crop planning tools such as the one developed is discussed. The simulator is outlined in detail while the schedule generator is touched upon briefly. The simulator consists of data inputs, plant and human models, and various other CELSS activity models such as food consumption and waste regeneration. The program inputs such as crew data and crop states are discussed. References are included for all nominal parameters used. Activities including harvesting, planting, plant respiration, and human respiration are discussed using mathematical models. Plans provided to the simulator by the plan generator are evaluated for their 'fitness' to the CELSS environment with an objective function based upon daily reservoir levels. Sample runs of the Crop Planning Tool and future needs for the tool are detailed.

Whitaker, Laura O.↗

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.↗

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.↗

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.↗

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↗

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↗

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↗

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↗

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.↗

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↗

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↗

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.↗

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↗

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.↗

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↗

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↗