Planning and scheduling is an important capability for a wide variety of NASA missions, serving either as an enabler without which the mission cannot be done at all, or serving to improve mission operations through making those operations more robust, more predictable, or more efficient.
The objective of this study was to provide input to strategic planning for planning and scheduling research and development within NASA. The rationale for employing an outside agent in this work was precisely to get that outside perspective, with no agenda or axe to grind regarding research priorities. The output of the study is the current report.

This report is intended to serve several purposes:

To provide a taxonomy of planning and scheduling functions relevant to NASA missions.
To provide an analysis of NASA missions currently planned or under study, with regard to the needs of those missions for planning and scheduling, in terms of that taxonomy.
To identify current or planned research and development within NASA or funded by NASA, addressing those identified needs.
To identify remaining unmet needs.

This report presents the results of an expert study to identify research opportunities for Sensors & Automation, a sub-program of the U.S. Department of Energy (DOE) Industrial Technologies Program (ITP). The research opportunities are prioritized by realizable energy savings. The study encompasses the technology areas of industrial controls, information processing, automation, and robotics. These areas have been central areas of focus of many Industries of the Future (IOF) technology roadmaps. This report identifies opportunities for energy savings as a direct result of advances in these areas and also recognizes indirect means of achieving energy savings, such as product quality improvement, productivity improvement, and reduction of recycle.

The Shared Human Computer Interaction Environment program is described with explored collaboration between humans and software agents operating in information-intensive, dynamic command and control applications. Combat search and rescue CSAR was the specific domain within which this research was conducted. Over the course of the three-year project, experts from numerous civilian and military organizations contributed to a detailed understanding of CSAR operations that influenced the vision, design, and implementation of the resulting system, the Search and Rescue Assistant SARA. Expert review indicated that, when implemented SARA would provide order of magnitude improvements to CSAR operations.

The Society of Automotive Engineers (SAE) Architecture Analysis & Design Language, AS5506, provides a means for the formal specification of the hardware and software architecture of embedded computer systems and system of systems. It was designed to support a full Model Based Development lifecycle including system specification, analysis, system tuning, integration, and upgrade over the lifecycle. It was designed to support the integration of multiple forms of analyses and to be extensible in a standard way for additional analysis approaches. A system can be automatically integrated from AADL models when fully specified and when source code is provided for the software components. Analysis of large complex systems has been demonstrated in the avionics domain.

In previous work, we have presented a novel global feasibility solver for the large system of quadratic constraints that arise as sub-problems in the solving of hard hybrid problems, such as the scheduling of refineries. In this paper we present the Gradient Optimal Constraint Equation Subdivision (GOCES) algorithm, which incorporates a standard NLP solver and the global feasibility solver to find and establish global optimums for systems of quadratic equations, and present benchmarks.

pddl was originally conceived and constructed as a lingua franca for the International Planning Competition. pddl2.1 embodies a set of extensions intended to support the expression of something closer to “real planning problems.” This objective has only been partially achieved, due in large part to a deliberate focus on not moving too far from classical planning models and solution methods.

Today, nearly one out of four households contain a family caregiver for someone over 50 years of age (MetLife, 2001). Nearly two-thirds of family caregivers work full or part-time, and over half of these caregivers report that they have had to make some sort of workplace accommodation, such as coming in late to work or leaving early, dropping back to part-time, turning down a promotion, choosing early retirement, or giving up work entirely to provide care. A key element in handling this explosion of the need for care is providing new products and services that allow individuals to cost effectively remain self-sufficient and continue to live in their own homes. Technology advances in sensors and communications has long promised to provide some of these capabilities. However, to date many of these needs remain unmet. We explore several dimensions of this issue looking at obstacles to technology insertion as well as the multiple motivators advocating solutions. We review a taxonomy of several systems that have been deployed into the market space and assess new trends. We conclude with recommendations for research that will drive the development of these enabling technologies.

Methods and systems are provided for enhancing the air quality in buildings during a chemical and/or biological attack and/or when the air quality around a building drops to unacceptable levels. Preferably, relatively non-contaminated (clean) air is stored in one or more clean air reservoirs. Once stored, the clean air is selectively delivered to buildings when a chemical and/or biological attack is detected, and/or when the air quality around a building drops to unacceptable levels.

We present a compositional approach to generate linear hybrid automata timing models, and Markovian stochastic automata safety models, from an architecture specification. Formal models declared for components are composed to form an overall model for the system, where the composition rules depend on the semantics of the architecture specification. We further allow abstract models to be specified for a subsystem of components, where the abstract model may be substituted for the concrete model of that subsystem when composing the overall system model. We assume both abstract and concrete models are given, we address the problem of verifying that the abstractions yield safe if approximate results. An abstract model may be viewed as a formal subsystem specification used for both conformance checking and improving the tractability of system analysis.

This report is the outcome of an investigation, funded by NASA’s Intelligent Systems program, into methods and means for using compiled automation to speed the development and deployment of increasingly autonomous spacecraft. Many NASA missions currently being planned or under study will require the deployment of an autonomous or semi-autonomous vehicle, which may be a deep-space probe (e.g., Galileo), a planetary rover (e.g., MER), or a lander (e.g., SAGE). Other missions may be possible without a greatly increased level of autonomy, but would still benefit from reduced operating costs, increased safety, and possibly greater science return, should that increased level of autonomy be practicable.