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At least 271 records · Page 15

SURE (Science User Resource Expert): A science planning and scheduling assistant for a resource based environment

SURE (Science User Resource Expert) is one of three components that compose the SURPASS (Science User Resource Planning and Scheduling System). This system is a planning and scheduling tool which supports distributed planning and scheduling, based on resource allocation and optimization. Currently SURE is being used within the SURPASS by the UARS (Upper Atmospheric Research Satellite) SOLSTICE instrument to build a daily science plan and activity schedule and in a prototyping effort with NASA GSFC to demonstrate distributed planning and scheduling for the SOLSTICE II instrument on the EOS platform. For the SOLSTICE application the SURE utilizes a rule-based system. Development of a rule-based program using Ada CLIPS as opposed to using conventional programming, allows for capture of the science planning and scheduling heuristics in rules and provides flexibility in inserting or removing rules as the scientific objectives and mission constraints change. The SURE system's role as a component in the SURPASS, the purpose of the SURE planning and scheduling tool, the SURE knowledge base, and the software architecture of the SURE component are described.

Thalman, Nancy E.↗

Integrating planning and reactive control

Artificial intelligence research on planning is concerned with designing control systems that choose actions by manipulating explicit descriptions of the world state, the goal to be achieved, and the effects of elementary operations available to the system. Because planning shifts much of the burden of reasoning to the machine, it holds great appeal as a high-level programming method. Experience shows, however, that it cannot be used indiscriminately because even moderately rich languages for describing goals, states, and the elementary operators lead to computational inefficiencies that render the approach unsuitable for realistic applications. This inadequacy has spawned a recent wave of research on reactive control or situated activity in which control systems are modeled as reacting directly to the current situation rather than as reasoning about the future effects of alternative action sequences. While this research has confronted the issue of run-time tractability head on, in many cases it has done so by sacrificing the advantages of declarative planning techniques. Ways in which the two approaches can be unified are discussed. The authors begin by modeling reactive control systems as state machines that map a stream of sensory inputs to a stream of control outputs. These machines can be decomposed into two continuously active subsystems: the planner and the execution module. The planner computes a plan, which can be seen as a set of bits that control the behavior of the execution module. An important element of this work is the formulation of a precise semantic interpretation for the inputs and outputs of the planning system. They show that the distinction between planned and reactive behavior is largely in the eye of the beholder: systems that seem to compute explicit plans can be redescribed in situation-action terms and vice versa. They also discuss practical programming techniques that allow the advantages of declarative programming and guaranteed reactive response to be achieved simultaneously.

Rosenschein, Stanley J.↗

Diagnosing faults in autonomous robot plan execution

A major requirement for an autonomous robot is the capability to diagnose faults during plan execution in an uncertain environment. Many diagnostic researches concentrate only on hardware failures within an autonomous robot. Taking a different approach, the implementation of a Telerobot Diagnostic System that addresses, in addition to the hardware failures, failures caused by unexpected event changes in the environment or failures due to plan errors, is described. One feature of the system is the utilization of task-plan knowledge and context information to deduce fault symptoms. This forward deduction provides valuable information on past activities and the current expectations of a robotic event, both of which can guide the plan-execution inference process. The inference process adopts a model-based technique to recreate the plan-execution process and to confirm fault-source hypotheses. This technique allows the system to diagnose multiple faults due to either unexpected plan failures or hardware errors. This research initiates a major effort to investigate relationships between hardware faults and plan errors, relationships which were not addressed in the past. The results of this research will provide a clear understanding of how to generate a better task planner for an autonomous robot and how to recover the robot from faults in a critical environment.

Lam, Raymond K.↗

Completable scheduling: An integrated approach to planning and scheduling

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.

Gervasio, Melinda T.↗

Mission activities planning for a Hermes mission by means of AI-technology

Mission Activities Planning is a complex task to be performed by mission control centers. AI technology can offer attractive solutions to the planning problem. This paper presents the use of a new AI-based Mission Planning System for crew activity planning. Based on a HERMES servicing mission to the COLUMBUS Man Tended Free Flyer (MTFF) with complex time and resource constraints, approximately 2000 activities with 50 different resources have been generated, processed, and planned with parametric variation of operationally sensitive parameters. The architecture, as well as the performance of the mission planning system, is discussed. An outlook to future planning scenarios, the requirements, and how a system like MARS can fulfill those requirements is given.

Pape, U.↗

Mission planning for an Earth observation low Earth orbiter: ERS-1

ERS-1, the first European Remote Sensing satellite, has a payload which consists primarily of microwave instruments and is in a polar sun-synchronous orbit. All ground and on-board activities from user requests to delivery of data products are combined into one integrated system. In view of the high number of products which can be generated by ERS-1, the Mission Planning System (MPS), which plans the on-board activities of ERS-1, is an essential tool for operations since manual planning of the large number of daily operations is out of the question. In addition the MPS, in line with the integrated nature of the ERS-1 system, also plans activities at the prime ground station, including among others, the operation of the payload data processing systems there. This paper outlines the operations concepts for ERS-1 mission planning, and describes the Mission Planning System used at the ERS-1 Control Center. Novel functionalities, such as automatic resource clash resolution, are described. A critical discussion gives lessons learned for future mission planning systems.

Lockyer, Paul↗

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↗

Joint operations planning for space surveillance missions on the MSX satellite

The Midcourse Space Experiment (MSX) satellite, sponsored by BMDO, is intended to gather broad-band phenomenology data on missiles, plumes, naturally occurring earthlimb backgrounds and deep space backgrounds. In addition the MSX will be used to conduct functional demonstrations of space-based space surveillance. The JHU/Applied Physics Laboratory (APL), located in Laurel, MD, is the integrator and operator of the MSX satellite. APL will conduct all operations related to the MSX and is charged with the detailed operations planning required to implement all of the experiments run on the MSX except the space surveillance experiments. The non-surveillance operations are generally amenable to being defined months ahead of time and being scheduled on a monthly basis. Lincoln Laboratory, Massachusetts Institute of Technology (LL), located in Lexington, MA, is the provider of one of the principle MSX instruments, the Space-Based Visible (SBV) sensor, and the agency charged with implementing the space surveillance demonstrations on the MSX. The planning timelines for the space surveillance demonstrations are fundamentally different from those for the other experiments. They are generally amenable to being scheduled on a monthly basis, but the specific experiment sequence and pointing must be refined shortly before execution. This allocation of responsibilities to different organizations implies the need for a joint mission planning system for conducting space surveillance demonstrations. This paper details the iterative, joint planning system, based on passing responsibility for generating MSX commands for surveillance operations from APL to LL for specific scheduled operations. The joint planning system, including the generation of a budget for spacecraft resources to be used for surveillance events, has been successfully demonstrated during ground testing of the MSX and is being validated for MSX launch within the year. The planning system developed for the MSX forms a model possibly applicable to developing distributed mission planning systems for other multi-use satellites.

Stokes, Grant↗

Backward assembly planning with DFA analysis

An assembly planning system that operates based on a recursive decomposition of assembly into subassemblies, and analyzes assembly cost in terms of stability, directionality, and manipulability to guide the generation of preferred assembly plans is presented. The planning in this system incorporates the special processes, such as cleaning, testing, labeling, etc. that must occur during the assembly, and handles nonreversible as well as reversible assembly tasks through backward assembly planning. In order to increase the planning efficiency, the system avoids the analysis of decompositions that do not correspond to feasible assembly tasks. This is achieved by grouping and merging those parts that can not be decomposable at the current stage of backward assembly planning due to the requirement of special processes and the constraint of interconnection feasibility. The invention includes methods of evaluating assembly cost in terms of the number of fixtures (or holding devices) and reorientations required for assembly, through the analysis of stability, directionality, and manipulability. All these factors are used in defining cost and heuristic functions for an AO* search for an optimal plan.

Lee, Sukhan↗

Intelligent Planning and Scheduling for Controlled Life Support Systems

Planning in Controlled Ecological Life Support Systems (CELSS) requires special look ahead capabilities due to the complex and long-term dynamic behavior of biological systems. This project characterizes the behavior of CELSS, identifies the requirements of intelligent planning systems for CELSS, proposes the decomposition of the planning task into short-term and long-term planning, and studies the crop scheduling problem as an initial approach to long-term planning. CELSS is studied in the realm of Chaos. The amount of biomass in the system is modeled using a bounded quadratic iterator. The results suggests that closed ecological systems can exhibit periodic behavior when imposed external or artificial control. The main characteristics of CELSS from the planning and scheduling perspective are discussed and requirements for planning systems are given. Crop scheduling problem is identified as an important component of the required long-term lookahead capabilities of a CELSS planner. The main characteristics of crop scheduling are described and a model is proposed to represent the problem. A surrogate measure of the probability of survival is developed. The measure reflects the absolute deviation of the vital reservoir levels from their nominal values. The solution space is generated using a probability distribution which captures both knowledge about the system and the current state of affairs at each decision epoch. This probability distribution is used in the context of an evolution paradigm. The concepts developed serve as the basis for the development of a simple crop scheduling tool which is used to demonstrate its usefulness in the design and operation of CELSS.

Leon, V. Jorge↗

Mars 2001 Lander Mission: Measurement Synergy Through Coordinated Operations Planning And Implementation

The 2001 Mars Surveyor Program Mission includes an orbiter with a gamma ray spectrometer and a multispectral thermal imager, and a lander with an extensive set of instrumentation, a robotic arm, and the Marie Curie Rover. The Mars 2001 Science Operations Working Group (SOWG) is a subgroup of the Project Science Group that has been formed to provide coordinated planning and implementation of scientific observations, particularly for the landed portion of the mission. The SOWG will be responsible for delivery of a science plan and, during operations, generation and delivery of conflict-free sequences. This group will also develop an archive plan that is compliant with Planetary Data System (PDS) standards, and will oversee generation, validation, and delivery of integrated archives to the PDS. In this report we cover one element of the SOWG planning activities, the development of a plan that maximizes the scientific return from lander-based observations by treating the instrument packages as an integrated payload. Scientific objectives for the lander mission have been defined. They include observations focused on determining the bedrock geology of the site through analyses of rocks and also local materials found in the soils, and the surficial geology of the site, including windblown deposits and the nature and history of formation of indurated sediments such as duricrust. Of particular interest is the identification and quantification of processes related to early warm, wet conditions and the presence of hydrologic or hydrothermal cycles. Determining the nature and origin of duricrust and associated salts is -very important in this regard. Specifically, did these deposits form in the vadose zone as pore water evaporated from soils or did they form by other processes, such as deposition of volcanic aerosols? Basic information needed to address these questions includes the morphology, topography, and geologic context of landforms and materials exposed at the site, together with quantitative information on material mineralogy, chemistry, and physical properties (rock textures; soil grain size and shape distributions; degree and nature of soil induration; soil magnetic properties). The calibration targets provide radiometric and mineralogical control surfaces. The magnets allow observations of magnetic phases. Patch plates are imaged to determine adhesive and abrasive properties of soils. Coordinated mission planning is crucial for optimizing the measurement synergy among the packages included on the lander. This planning has already begun through generation of multi-sol detailed operations activities. One focus has been to develop a scenario to use the arm to dig a soil trench to a depth of tens of centimeters. The activity will be monitored through use of Pancam and RAC to ensure nominal operations and to acquire data to determine subsurface physical properties (e.g., angle of repose of trench walls). Pancam and Mini-TES observations would also provide constraints on mineralogy and texture for the walls and bottom of the trench during excavation. If desired, soils excavated at depth could be deposited on the surface and Mossbauer and APXS measurements could be acquired for these materials. Soil samples from various depths would be delivered to MECA for characterization of aqueous geochemistry and physical properties of soil grains, particularly size, shape, and hardness. These physical properties would be determined by optical and atomic force microscopy. When completed, detailed information of soil properties as a function of depth would be obtained. These various data sets would constrain our understanding of whether or not there are systematic variations in soil characteristics as a function of depth. These variations might be related, for example, to evaporative moisture losses and formation of salt deposits, thereby indicating water transport processes occurred fairly recently. Many other value-added measurement scenarios are being developed. For example, characterizing the nature and dynamics of dust deposition will be done using MIP/DART to provide deposition rates, Pancam and RAC imaging of lander and rover surfaces to extrapolate these measurements to other areas, and a variety of measurements to determine if the bulk loose soil has the same characteristics as dust that accumulates during the mission. Bedrock geology of the site is primarily an APEX-focus setting, mineralogy, and texture, and APXS data to be we interest will be to determine the extent to which rock hydrothermal processes, given that APEX is the precursor 4 and 2005 rover missions. Additional information is contained in the original.

Arvidson, R.↗

Automated Planning for a Deep Space Communications Station

This paper describes the application of Artificial Intelligence planning techniques to the problem of antenna track plan generation for a NASA Deep Space Communications Station. Me described system enables an antenna communications station to automatically respond to a set of tracking goals by correctly configuring the appropriate hardware and software to provide the requested communication services. To perform this task, the Automated Scheduling and Planning Environment (ASPEN) has been applied to automatically produce antenna trucking plans that are tailored to support a set of input goals. In this paper, we describe the antenna automation problem, the ASPEN planning and scheduling system, how ASPEN is used to generate antenna track plans, the results of several technology demonstrations, and future work utilizing dynamic planning technology.

Estlin, Tara↗

NASA Performance Plan

The Government Performance and Results Act (GPRA) passed by Congress and signed by the President in 1993 provides a new tool to improve the efficiency of all Federal agencies. The goals of GPRA are to: Improve citizen confidence in Government performance; Improve Federal program management, effectiveness, and public accountability; and Improve congressional decisionmaking on where to commit the Nation's financial and human resources. The Act directs Executive Branch agencies to develop a customer-focused strategic plan that aligns activities with concrete missions and goals. The first plans were submitted in September 1998 as part of the Fiscal Year 1999 (FY99) budget process. These budget submissions were expected to support the goals expressed in the agency strategic plans. The Act also directs agencies to manage and measure results to justify congressional appropriations and authorizations. Six months after the completion of the fiscal year, agencies will report on the degree of success in achieving the goals and evaluation measures defined in the strategic and performance plans. The plans required by GPRA have been submitted to the Office of Management and Budget (OMB) and to Congress. Copies of NASA plans are available from the Office of Policy and Plans at NASA Headquarters and can be accessed on the i nterinet web sites identified in the Appendix.

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Fast Transformation of Temporal Plans for Efficient Execution

Temporal plans permit significant flexibility in specifying the occurrence time of events. Plan execution can make good use of that flexibility. However, the advantage of execution flexibility is counterbalanced by the cost during execution of propagating the time of occurrence of events throughout the flexible plan. To minimize execution latency, this propagation needs to be very efficient. Previous work showed that every temporal plan can be reformulated as a dispatchable plan, i.e., one for which propagation to immediate neighbors is sufficient. A simple algorithm was given that finds a dispatchable plan with a minimum number of edges in cubic time and quadratic space. In this paper, we focus on the efficiency of the reformulation process, and improve on that result. A new algorithm is presented that uses linear space and has time complexity equivalent to Johnson s algorithm for all-pairs shortest-path problems. Experimental evidence confirms the practical effectiveness of the new algorithm. For example, on a large commercial application, the performance is improved by at least two orders of magnitude. We further show that the dispatchable plan, already minimal in the total number of edges, can also be made minimal in the maximum number of edges incoming or outgoing at any node.

Tsamardinos, Ioannis↗

Activity Planning for the Mars Exploration Rovers

Operating the Mars Exploration Rovers is a challenging, time-pressured task. Each day, the operations team must generate a new plan describing the rover activities for the next day. These plans must abide by resource limitations, safety rules, and temporal constraints. The objective is to achieve as much science as possible, choosing from a set of observation requests that oversubscribe rover resources. In order to accomplish this objective, given the short amount of planning time available, the MAPGEN (Mixed-initiative Activity Plan GENerator) system was made a mission-critical part of the ground operations system. MAPGEN is a mixed-initiative system that employs automated constraint-based planning, scheduling, and temporal reasoning to assist operations staff in generating the daily activity plans. This paper describes the adaptation of constraint-based planning and temporal reasoning to a mixed-initiative setting and the key technical solutions developed for the mission deployment of MAPGEN.

Bresina, John L.↗

Experimental Evaluation of a Planning Language Suitable for Formal Verification

The marriage of model checking and planning faces two seemingly diverging alternatives: the need for a planning language expressive enough to capture the complexity of real-life applications, as opposed to a language simple, yet robust enough to be amenable to exhaustive verification and validation techniques. In an attempt to reconcile these differences, we have designed an abstract plan description language, ANMLite, inspired from the Action Notation Modeling Language (ANML) [17]. We present the basic concepts of the ANMLite language as well as an automatic translator from ANMLite to the model checker SAL (Symbolic Analysis Laboratory) [7]. We discuss various aspects of specifying a plan in terms of constraints and explore the implications of choosing a robust logic behind the specification of constraints, rather than simply propose a new planning language. Additionally, we provide an initial assessment of the efficiency of model checking to search for solutions of planning problems. To this end, we design a basic test benchmark and study the scalability of the generated SAL models in terms of plan complexity.

Butler, Rick W.↗

Walking the Walk/Talking the Talk: Mission Planning with Speech-Interactive Agents

The application of simulation technology to mission planning and rehearsal has enabled realistic overhead 2-D and immersive 3-D "fly-through" capabilities that can help better prepare tactical teams for conducting missions in unfamiliar locales. For aircrews, detailed terrain data can offer a preview of the relevant landmarks and hazards, and threat models can provide a comprehensive glimpse of potential hot zones and safety corridors. A further extension of the utility of such planning and rehearsal techniques would allow users to perform the radio communications planned for a mission; that is, the air-ground coordination that is critical to the success of missions such as close air support (CAS). Such practice opportunities, while valuable, are limited by the inescapable scarcity of complete mission teams to gather in space and time during planning and rehearsal cycles. Moreoever, using simulated comms with synthetic entities, despite the substantial training and cost benefits, remains an elusive objective. In this paper we report on a solution to this gap that incorporates "synthetic teammates" - intelligent software agents that can role-play entities in a mission scenario and that can communicate in spoken language with users. We employ a fielded mission planning and rehearsal tool so that our focus remains on the experimental objectives of the research rather than on developing a testbed from scratch. Use of this planning tool also helps to validate the approach in an operational system. The result is a demonstration of a mission rehearsal tool that allows aircrew users to not only fly the mission but also practice the verbal communications with air control agencies and tactical controllers on the ground. This work will be presented in a CAS mission planning example but has broad applicability across weapons systems, missions and tactical force compositions.

Bell, Benjamin↗

Traverse Planning Experiments for Future Planetary Surface Exploration

This paper describes the results of a recent (July-August 2010 and July 2011) planetary surface traverse planning experiment. The purpose of this experiment was to gather data relevant to robotically repositioning surface assets used for planetary surface exploration. This is a scenario currently being considered for future human exploration missions to the Moon and Mars. The specific scenario selected was a robotic traverse on the lunar surface from an outpost at Shackleton Crater to the Malapert Massif. As these are exploration scenarios, the route will not have been previously traversed and the only pre-traverse data sets available will be remote (orbital) observations. Devon Island was selected as an analog location where a traverse route of significant length could be planned and then traveled. During the first half of 2010, a team of engineers and scientists who had never been to Devon Island used remote sensing data comparable to that which is likely to be available for the Malapert region (eg., 2-meter/pixel imagery, 10-meter interval topographic maps and associated digital elevation models, etc.) to plan a 17-kilometer (km) traverse. Surface-level imagery data was then gathered on-site that was provided to the planning team. This team then assessed whether the route was actually traversable or not. Lessons learned during the 2010 experiment were then used in a second experiment in 2011 for which a much longer traverse (85 km) was planned and additional surface-level imagery different from that gathered in 2010 was obtained for a comparative analysis. This paper will describe the route planning techniques used, the data sets available to the route planners and the lessons learned from the two traverses planned and carried out on Devon Island.

Hoffman, S. J.↗