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Smith, Jeffrey H.

Publications and source records attributed to Smith, Jeffrey H..

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler

HURON solves the problem of how to optimize a plan and schedule for assigning multiple agents to a temporal sequence of actions (e.g., science tasks). Developed as a generic planning and scheduling tool, HURON has been used to optimize space mission surface operations. The tool has also been used to analyze lunar architectures for a variety of surface operational scenarios in order to maximize return on investment and productivity. These scenarios include numerous science activities performed by a diverse set of agents: humans, teleoperated rovers, and autonomous rovers. Once given a set of agents, activities, resources, resource constraints, temporal constraints, and de pendencies, HURON computes an optimal schedule that meets a specified goal (e.g., maximum productivity or minimum time), subject to the constraints. HURON performs planning and scheduling optimization as a graph search in state-space with forward progression. Each node in the graph contains a state instance. Starting with the initial node, a graph is automatically constructed with new successive nodes of each new state to explore. The optimization uses a set of pre-conditions and post-conditions to create the children states. The Python language was adopted to not only enable more agile development, but to also allow the domain experts to easily define their optimization models. A graphical user interface was also developed to facilitate real-time search information feedback and interaction by the operator in the search optimization process. The HURON package has many potential uses in the fields of Operations Research and Management Science where this technology applies to many commercial domains requiring optimization to reduce costs. For example, optimizing a fleet of transportation truck routes, aircraft flight scheduling, and other route-planning scenarios involving multiple agent task optimization would all benefit by using HURON.

Hua, Hook↗
NASA NTRS2012

NASA'S concept for a human mission to a near-earth asteroid : preference tradeoffs for the surveyor decision problem

NASA's recent attention and interest in sending a human mission to land on a Near-Earth asteroid raised the question of whether to first send a robotic surveyor. This paper describes a Bayesian approach for comparing the value and cost-risk tradeoffs of sending (versus not sending) surveyor missions prior to a human mission. A multiattribute decision analysis approach was used to account for both mission value and cost in each of 27 hypothetical risk-attitude cases corresponding to an emphasis on mission value; equal priority between mission value and cost; and an emphasis on cost. The decisions implied by the different strategic viewpoints are described.

Smith, Jeffrey H.↗
NASA NTRS2011

Reducing the Risk and Improving Mission Success for NASA's Human Mission to a Near-Earth Asteroid: How Many Robotic Surveyors?

NASA's recent attention and interest in sending a human mission to land on a Near-Earth asteroid raises the question of need for a robotic surveyor. This paper describes a Bayesian approach for comparing the productivity and cost-risk tradeoffs of sending (versus not sending) one or more robotic surveyor missions prior to a human mission to land on an asteroid. The probability of finding an asteroid suitable for landing was derived from an analysis of more than 1200 asteroids in order to define a quantitative estimate of suitability. The low cost of the surveyors relative to the human mission underlined the multi-surveyor strategy as relatively inexpensive insurance against the risks of encountering an unsuitable asteroid for landing on arrival by a human mission.

decision analysis↗
NASA NTRS2011

Geo-Statistical Approach to Estimating Asteroid Exploration Parameters

NASA's vision for space exploration calls for a human visit to a near earth asteroid (NEA). Potential human operations at an asteroid include exploring a number of sites and analyzing and collecting multiple surface samples at each site. In this paper two approaches to formulation and scheduling of human exploration activities are compared given uncertain information regarding the asteroid prior to visit. In the first approach a probability model was applied to determine best estimates of mission duration and exploration activities consistent with exploration goals and existing prior data about the expected aggregate terrain information. These estimates were compared to a second approach or baseline plan where activities were constrained to fit within an assumed mission duration. The results compare the number of sites visited, number of samples analyzed per site, and the probability of achieving mission goals related to surface characterization for both cases.

probability↗
NASA NTRS2011

NASA's Human Mission to a Near-Earth Asteroid: Landing on a Moving Target

This paper describes a Bayesian approach for comparing the productivity and cost-risk tradeoffs of sending versus not sending one or more robotic surveyor missions prior to a human mission to land on an asteroid. The expected value of sample information based on productivity combined with parametric variations in the prior probability an asteroid might be found suitable for landing were used to assess the optimal number of spacecraft and asteroids to survey. The analysis supports the value of surveyor missions to asteroids and indicates one launch with two spacecraft going simultaneously to two independent asteroids appears optimal.

precursor decision making↗
NASA NTRS2010

Reconciling Scientific Aspirations and Engineering Constraints for a Lunar Mission via Hyperdimensional Interpolation

Virtually every NASA space-exploration mission represents a compromise between the interests of two expert, dedicated, but very different communities: scientists, who want to go quickly to the places that interest them most and spend as much time there as possible conducting sophisticated experiments, and the engineers and designers charged with maximizing the probability that a given mission will be successful and cost-effective. Recent work at NASA's Jet Propulsion Laboratory (JPL) seeks to enhance communication between these two groups, and to help them reconcile their interests, by developing advanced modeling capabilities with which they can analyze the achievement of science goals and objectives against engineering design and operational constraints. The analyses conducted prior to this study have been point-design driven. Each analysis has been of one hypothetical case which addresses the question: Given a set of constraints, how much science can be done? But the constraints imposed by the architecture team-e.g., rover speed, time allowed for extravehicular activity (EVA), number of sites at which science experiments are to be conducted- are all in early development and carry a great deal of uncertainty. Variations can be incorporated into the analysis, and indeed that has been done in sensitivity studies designed to see which constraint variations have the greatest impact on results. But if a very large number of variations can be analyzed all at once, producing a table that includes virtually the entire trade space under consideration, then we have a tool that enables scientists and mission architects to ask the inverse question: For a given desired level of science (or any other objective), what is the range of constraints that would be needed? With this tool, mission architects could determine, for example, what combinations of rover speed, EVA duration, and other constraints produce the desired results. Further, this tool would help them identify which technology-improvement investments would be likely to produce the largest or most important return. However, the number of variations that need to be considered for such analysis quickly balloons to an unwieldy size. If three variations are considered for each of six constraints-a very modest example-there are a total of 243 variations to consider. If it takes 40 minutes to compute each variation, as it does with HURON, our automated optimization system, then it would take 162 hours or nearly 7 days of round-the-clock computing to calculate the results. Adding further constraints or variations exponentially increases the amount of time that is needed.

Weisbin, Charles R.↗
NASA NTRS2006

In-situ resource utilization for the human exploration of Mars : a Bayesian approach to valuation of precursor missions

The need for sufficient quantities of oxygen, water, and fuel resources to support a crew on the surface of Mars presents a critical logistical issue of whether to transport such resources from Earth or manufacture them on Mars. An approach based on the classical Wildcat Drilling Problem of Bayesian decision theory was applied to the problem of finding water in order to compute the expected value of precursor mission sample information. An implicit (required) probability of finding water on Mars was derived from the value of sample information using the expected mass savings of alternative precursor missions.

water↗
NASA NTRS2006

Methodology for evaluating modular assembly of large space platforms

This paper presents a methodology for analytically comparing approaches to modular assembly of large space platforms. the methodology combines a physical model of the modules, a life-cycle cost model, and a risk model to capture influential trade-offs.

in-space construction↗
NASA NTRS2004

Toward a Systematic Approach for Selection of NASA Technology Portfolios

There is an important need for a consistent analytical foundation supporting the selection and monitoring of R&D tasks that support new system concepts that enable future NASA missions. This capability should be applicable at various degrees of abstraction, depending upon whether one is interested in formulation, development, or operations. It should also be applicable to a single project, a program comprised of a group of projects, an enterprise typically including multiple programs, and the overall agency itself. Emphasis here is on technology selection and new initiatives, but the same approach can be generalized to other applications, dealing, for example, with new system architectures, risk reduction, and task allocation among humans and machines. The purpose of this paper is to describe one such approach, which is in its early stages of implementation within NASA programs, and to discuss several illustrative examples.

return on investment↗
NASA NTRS2004

A decision support system for technology R&D planning: connecting the dots from information to innovation

This paper describes an information technology innovation developed to assist decision makers faced with complex R&D tasks. The decision support system (DSS) was developed and applied to the analysis of a 10-year, 700 million dollar technology program for the exploration of Mars. The technologies were to enable a 4.8 billion dollar portfolio of exploration flight missions to Mars.

DSS↗
NASA NTRS2001

E-Scheduling the Deep Space Network

This paper describes an operations concept for electronic scheduling and software interface for organizations to extract required views of the schedule. Advantages include widespread accessibility to a common schedule document, virtually instantaneous distribution of new schedule releases, and the ability of missions to perfom conflict resolution off-line without time-consuming meetings.

telecommunications↗
NASA NTRS1992

Decision rules for spaceborne operations planning

Recent study of Space Station Freedom requirements for extravehicular activity (EVA) to perform external maintenance tasks emphasize an oversubscription of resources for performing on-orbit tasks. Extravehicular robotics (EVR) and cooperative EVA combined with EVR (using crew and robots synergistically to perform tasks) have been suggested as a part of the solution to reduce EVA. The question remains however, 'Under what conditions is it cost-effective to use the EVA and/or EVR resource.' The answer to such a question also has implications for the Space Station Freedom and its external maintenance as well as the Space Exploration Initiative (SEI) where the issue of work-system allocation is magnified by the long distances and scope of EVA work. This paper describes a simple technique of interest to operational planners and robot technology planners for determining in an economic context whether to use EVA alone, EVR alone, or Cooperative EVA. It is also shown that given: (1) the task times for these alternatives; and (2) the marginal costs of EVA, EVR, and IVA, the appropriate work system for performing the task can be identified. The paper illustrates how the work system choice is based on the ratio of costs. An example using Space Station Freedom data is presented to illustrate the trade-offs among alternative work-systems.

Smith, Jeffrey H.↗
NASA NTRS1992

Directions for lunar construction - A derivation of requirements from a construction scenario analysis

This paper provides an initial trade-off study among several lunar construction options available to the Space Exploration Initiative. The relative time effectiveness of Extra-Vehicular Activity (EVA), Intra-Vehicular Activity (IVA), and Earth-based remote control assembly and construction methods are studied. Also considered is whether there is any construction time savings to building roads in advance, or surveying the construction sites with orbiters or rovers in advance. The study was conducted by adding detail to a potentially real scenario - a nuclear power plant - and applying time multipliers for the various control options and terrain alternatives, provided by roboticists among the authors. The authors conclude that IVA is a faster construction method than either EVA or construction conducted remotely from Earth. Surveying proposed sites in advance, with orbiters and rovers, provides a significant time savings through adding to certainty, and therefore may be cost effective. Developing a heavy-lift launch capability and minimizing assembly and construction processes by landing large payloads is probably worthwhile to the degree possible, as construction activities would use a large amount of surface operations time.

Dias, William S.↗
NASA NTRS1992

Spaceborne construction and operations planning - Decision rules for selecting EVA, telerobot, and combined work-systems

An approach is presented for selecting an appropriate work-system for performing construction and operations tasks by humans and telerobots. The decision to use extravehicular activity (EVA) performed by astronauts, extravehicular robotics (EVR), or a combination of EVA and EVR is determined by the ratio of the marginal costs of EVA, EVR, and IVA. The approach proposed here is useful for examining cost trade-offs between tasks and performing trade studies of task improvement techniques (human or telerobotic).

Smith, Jeffrey H.↗
NASA NTRS1991

Software For Integration Of EVA And Telerobotics

Telerobotics/EVA Joint Analysis Systems (TEJAS) computer program is hypermedia information software system using object-oriented programming to bridge gap between crew-EVA and telerobotics activities. TEJAS Version 1.0 contains 20 HyperCard stacks using visual, customizable interface of icon buttons, pop-up menus, and relational commands to store, link, and standardize related information about primitives, technologies, tasks, assumptions, and open issues involved in space-telerobot or crew-EVA tasks. Runs on any Apple MacIntosh personal computer.

Drews, Michael L.↗
NASA NTRS1990

An application of multiattribute decision analysis to the Space Station Freedom program. Case study: Automation and robotics technology evaluation

The results are described of an application of multiattribute analysis to the evaluation of high leverage prototyping technologies in the automation and robotics (A and R) areas that might contribute to the Space Station (SS) Freedom baseline design. An implication is that high leverage prototyping is beneficial to the SS Freedom Program as a means for transferring technology from the advanced development program to the baseline program. The process also highlights the tradeoffs to be made between subsidizing high value, low risk technology development versus high value, high risk technology developments. Twenty one A and R Technology tasks spanning a diverse array of technical concepts were evaluated using multiattribute decision analysis. Because of large uncertainties associated with characterizing the technologies, the methodology was modified to incorporate uncertainty. Eight attributes affected the rankings: initial cost, operation cost, crew productivity, safety, resource requirements, growth potential, and spinoff potential. The four attributes of initial cost, operations cost, crew productivity, and safety affected the rankings the most.

Smith, Jeffrey H.↗
NASA NTRS1990

Advanced Robotics for In-Space Vehicle Processing

An analysis of spaceborne vehicle processing is described. Generic crew-EVA tasks are presented for a specific vehicle, the orbital maneuvering vehicle (OMV), with general implications to other on-orbit vehicles. The OMV is examined with respect to both servicing and maintenance. Crew-EVA activities are presented by task and mapped to a common set of generic crew-EVA primitives to identify high-demand areas for telerobot services. Similarly, a set of telerobot primitives is presented that can be used to model telerobot actions for alternative telerobot reference configurations. The telerobot primitives are tied to technologies and used for composting telerobot operations for an automated refueling scenario. Telerobotics technology issues and design accomodation guidelines (hooks and scars) for the Space Station Freedom are described.

Smith, Jeffrey H.↗