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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

An approach to rescheduling activities based on determination of priority and disruptivity

A constraint-based scheduling system called SPIKE is being used to create long term schedules for the Hubble Space Telescope. Feedback for the spacecraft or from other ground support systems may invalidate some scheduling decisions and those activities concerned must be reconsidered. A function rescheduling priority is defined which for a given activity performs a heuristic analysis and produces a relative numerical value which is used to rank all such entities in the order that they should be rescheduled. A function disruptivity is also defined that is used to place a relative numeric value on how much a pre-existing schedule would be changed in order to reschedule an activity. Using these functions, two algorithms (a stochastic neural network approach and an exhaustive search approach) are proposed to find the best place to reschedule an activity. Prototypes were implemented and preliminary testing reveals that the exhaustive technique produces only marginally better results at much greater computational cost.

Sponsler, Jeffrey L.↗

Contingency rescheduling of spacecraft operations

Spacecraft activity scheduling was a focus of attention in artificial intelligence recently. Several scheduling systems were devised which more-or-less successfully address various aspects of the activity scheduling problem, though most of these are not yet mature, with the notable expection of NASA's ESP. Few current scheduling systems, however, make any attempt to deal fully with the problem of modifying a schedule in near-real-time in the event of contingencies which may arise during schedule execution. These contingencies can include resources becoming unavailable unpredictably, a change in spacecraft conditions or environment, or the need to perform an activity not scheduled. In these cases it becomes necessary to repair an existing schedule, disrupting ongoing operations as little as possible. Normal scheduling is just a part of that which must be accomplished during contingency rescheduling. A prototype system named MAESTRO was developed for spacecraft activity scheduling. MAESTRO is briefly described with a focus on recent work in the area of real-time contingency handling. Included is a discussion of some of the complexities of the scheduling problem and how they affect contingency rescheduling, such as temporal constraints between activities, activities which may be interrupted and continued in any of several ways, and different ways to choose a resource complement which will allow continuation of an activity. Various heuristics used in MAESTRO for contingency rescheduling is discussed, as are operational concerns such as interaction of the scheduler with spacecraft subsystems controllers.

Britt, Daniel L.↗

The Path to Crew Autonomy - Situational Awareness in Scheduling and Rescheduling Tasks for Novice Schedulers

To increase crew autonomy for long duration exploration-class missions (LDEM), certain mission support tasks need to be completed by crew. Currently, crew activities are scheduled over the course of several weeks by ground-based experts with years of experience-based training. These experts display extensive amounts of situational awareness (SA) throughout task execution by maintaining a mental model of additional factors during scheduling such as constraints (e.g. physical space/layout), abilities and skills of the crew, and crew preferences allowing them to anticipate and mitigate potential issues. Thus, situational awareness is a key component for crews to manage their own schedules. In this paper, we examined situational awareness in novice schedulers in both a scheduling and rescheduling task. Our findings indicate that there is no significant difference between scheduling and rescheduling tasks for the development of SA in novice schedulers. Additionally, our experiment shows that novice schedulers are less able to develop sufficient SA for constraints that are dependent on one or more activities. Thus, we propose that software aids may be useful to support novice schedulers and increase SA in scheduling/rescheduling tasks. This work is vital to ensure the successful transfer of mission support tasks to the crew for future LDEM.

situation awareness↗

Scheduling and rescheduling with iterative repair

This paper describes the GERRY scheduling and rescheduling system being applied to coordinate Space Shuttle Ground Processing. The system uses constraint-based iterative repair, a technique that starts with a complete but possibly flawed schedule and iteratively improves it by using constraint knowledge within repair heuristics. In this paper we explore the tradeoff between the informedness and the computational cost of several repair heuristics. We show empirically that some knowledge can greatly improve the convergence speed of a repair-based system, but that too much knowledge, such as the knowledge embodied within the MIN-CONFLICTS lookahead heuristic, can overwhelm a system and result in degraded performance.

Zweben, Monte↗

Rescheduling with iterative repair

This paper presents a new approach to rescheduling called constraint-based iterative repair. This approach gives our system the ability to satisfy domain constraints, address optimization concerns, minimize perturbation to the original schedule, produce modified schedules, quickly, and exhibits 'anytime' behavior. The system begins with an initial, flawed schedule and then iteratively repairs constraint violations until a conflict-free schedule is produced. In an empirical demonstration, we vary the importance of minimizing perturbation and report how fast the system is able to resolve conflicts in a given time bound. We also show the anytime characteristics of the system. These experiments were performed within the domain of Space Shuttle ground processing.

Zweben, Monte↗

Rescheduling with iterative repair

This paper presents a new approach to rescheduling called constraint-based iterative repair. This approach gives our system the ability to satisfy domain constraints, address optimization concerns, minimize perturbation to the original schedule, and produce modified schedules quickly. The system begins with an initial, flawed schedule and then iteratively repairs constraint violations until a conflict-free schedule is produced. In an empirical demonstration, we vary the importance of minimizing perturbation and report how fast the system is able to resolve conflicts in a given time bound. These experiments were performed within the domain of Space Shuttle ground processing.

Zweben, Monte↗

Multi-agent planning and scheduling, execution monitoring and incremental rescheduling: Application to motorway traffic

This article describes a planning method applicable to agents with great perception and decision-making capabilities and the ability to communicate with other agents. Each agent has a task to fulfill allowing for the actions of other agents in its vicinity. Certain simultaneous actions may cause conflicts because they require the same resource. The agent plans each of its actions and simultaneously transmits these to its neighbors. In a similar way, it receives plans from the other agents and must take account of these plans. The planning method allows us to build a distributed scheduling system. Here, these agents are robot vehicles on a highway communicating by radio. In this environment, conflicts between agents concern the allocation of space in time and are connected with the inertia of the vehicles. Each vehicle made a temporal, spatial, and situated reasoning in order to drive without collision. The flexibility and reactivity of the method presented here allows the agent to generate its plan based on assumptions concerning the other agents and then check these assumptions progressively as plans are received from the other agents. A multi-agent execution monitoring of these plans can be done, using data generated during planning and the multi-agent decision-making algorithm described here. A selective backtrack allows us to perform incremental rescheduling.

Mourou, Pascal↗

Aerial Refueling Process Rescheduling Under Job Related Disruptions

The Aerial Refueling Scheduling Problem (ARSP) can be defined as determining the refueling completion times for each fighter aircraft (job) on the multiple tankers (machines) to minimize the total weighted tardiness. ARSP assumes that the jobs have different release times and due dates. The ARSP is dynamic environment and unexpected events may occur. In this paper, rescheduling in the aerial refueling process with a time set of jobs will be studied to deal with job related disruptions such as the arrival of new jobs, the departure of an existing job, high deviations in the release times and changes in job priorities. In order to keep the stability and to avoid excessive computation, partial schedule repair algorithm is developed and its preliminary results are presented.

Kaplan, Sezgin↗

Iterative repair for scheduling and rescheduling

An iterative repair search method is described called constraint based simulated annealing. Simulated annealing is a hill climbing search technique capable of escaping local minima. The utility of the constraint based framework is shown by comparing search performance with and without the constraint framework on a suite of randomly generated problems. Results are also shown of applying the technique to the NASA Space Shuttle ground processing problem. These experiments show that the search methods scales to complex, real world problems and reflects interesting anytime behavior.

Zweben, Monte↗

Interleaved Observation Execution and Rescheduling on Earth Observing Systems

Observation scheduling for Earth orbiting satellites solves the following problem: given a set of requests for images of the Earth, a set of instruments for acquiring those images distributed on a collecting of orbiting satellites, and a set of temporal and resource constraints, generate a set of assignments of instruments and viewing times to those requests that satisfy those constraints. Observation scheduling is often construed as a constrained optimization problem with the objective of maximizing the overall utility of the science data acquired. The utility of an image is typically based on the intrinsic importance of acquiring it (for example, its importance in meeting a mission or science campaign objective) as well as the expected value of the data given current viewing conditions (for example, if the image is occluded by clouds, its value is usually diminished). Currently, science observation scheduling for Earth Observing Systems is done on the ground, for periods covering a day or more. Schedules are uplinked to the satellites and are executed rigorously. An alternative to this scenario is to do some of the decision-making about what images are to be acquired on-board. The principal argument for this capability is that the desirability of making an observation can change dynamically, because of changes in meteorological conditions (e.g. cloud cover), unforeseen events such as fires, floods, or volcanic eruptions, or un-expected changes in satellite or ground station capability. Furthermore, since satellites can only communicate with the ground between 5% to 10% of the time, it may be infeasible to make the desired changes to the schedule on the ground, and uplink the revisions in time for the on-board system to execute them. Examples of scenarios that motivate an on-board capability for revising schedules include the following. First, if a desired visual scene is completely obscured by clouds, then there is little point in taking it. In this case, satellite resources, such as power and storage space can be better utilized taking another image that is higher quality. Second, if an unexpected but important event occurs (such as a fire, flood, or volcanic eruption), there may be good reason to take images of it, instead of expending satellite resources on some of the lower priority scheduled observations. Finally, if there is unexpected loss of capability, it may be impossible to carry out the schedule of planned observations. For example, if a ground station goes down temporarily, a satellite may not be able to free up enough storage space to continue with the remaining schedule of observations. This paper describes an approach for interleaving execution of observation schedules with dynamic schedule revision based on changes to the expected utility of the acquired images. We describe the problem in detail, formulate an algorithm for interleaving schedule revision and execution, and discuss refinements to the algorithm based on the need for search efficiency. We summarize with a brief discussion of the tests performed on the system.

Khatib, Lina↗