A methodology to determine impact of robotic technologies on space exploration missions
This paper presents a new method for evaluating relative strengths and impact of robotic technologies utilized for space exploration missions.
Engineering topics
Publications and source records attributed to Drummond, Mark.
This paper presents a new method for evaluating relative strengths and impact of robotic technologies utilized for space exploration missions.
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This paper presents a technique for building robust telescope schedules that tend not to break. The technique is called Just-In-Case (JIC) scheduling and it implements the common sense idea of being prepared for likely errors, just in case they should occur. The JIC algorithm analyzes a given schedule, determines where it is likely to break, reinvokes a scheduler to generate a contingent schedule for each highly probable break case, and produces a 'multiply contingent' schedule. The technique was developed for an automatic telescope scheduling problem, and the paper presents empirical results showing that Just-In-Case scheduling performs extremely well for this problem.
This paper outlines a new telescope operations model that is intended to achieve low operating costs with high operating efficiency and high scientific productivity. The model is based on the existing Principal Astronomer approach used in conjunction with ATIS, a language for commanding remotely located automatic telescopes. This paper introduces the notion of an Associate Principal Astronomer, or APA. At the heart of the APA is automatic observation loading and scheduling software, and it is this software that is expected to help achieve efficient and productive telescope operations. The purpose of the APA system is to make it possible for astronomers to submit observation requests to and obtain resulting data from remote automatic telescopes, via the Internet, in a highly-automated way that minimizes human interaction with the system and maximizes the scientific return from observing time.
Some applications involve automatic generation and execution of schedules that contain actions with uncertain durations. Such uncertainty can cause schedules to break during execution. This paper presents a technique, called Just-In-Case scheduling or JIC, for building robust schedules that tend not to break. The technique implements the common sense idea of being prepared for likely errors, just in case they should occur. The JIC algorithm analyzes a given schedule, determines where it is likely to break, reinvokes the scheduler to generate a contingent schedule for each highly probable break case, and produces a "multiply contingent" schedule. The technique was developed for a real telescope scheduling problem, and the paper presents empirical results showing that Just-In-Case scheduling performs extremely well for this problem.
This paper presents a technique for statistically characterizing a search space and demonstrates the use of this technique within a practical telescope scheduling application. The characterization provides the following: (i) an estimate of the search space size, (ii) a scaling technique for multi-attribute objective functions and search heuristics, (iii) a "quality density function" for schedules in a search space, (iv) a measure of a scheduler's performance, and (v) support for constructing and tuning search heuristics. This paper describes the random sampling algorithm used to construct this characterization and explains how it can be used to produce this information. As an example, we include a comparative analysis of an heuristic dispatch scheduler and a look-ahead scheduler that performs greedy search.
NASA TileWorld (NTW) computer program formulated to further research on planning, scheduling, and control problems. Designed to focus on three particular attributes of real-world problems: exogenous events, uncertain outcomes of actions, and metric time. Written specifically for use by NASA, NTW modified easily to act as software base for other simulated environments. Written in Allegro Common Lisp for Sun-3-(TM) and Sun-4-series(TM) computers running SunOS(TM).
The purpose is to describe the applications of Artificial Intelligence (AI) to the European Space program that are being developed or have been developed. The results of a study sponsored by the Artificial Intelligence Research and Development program of NASA's Office of Advanced Concepts and Technology (OACT) are described. The report is divided into two sections. The first consists of site reports, which are descriptions of the AI applications seen at each place visited. The second section consists of two summaries which synthesize the information in the site reports by organizing this information in two different ways. The first organizes the material in terms of the type of application, e.g., data analysis, planning and scheduling, and procedure management. The second organizes the material in terms of the component technologies of Artificial Intelligence which the applications used, e.g., knowledge based systems, model based reasoning, procedural reasoning, etc.
Automatic Photoelectric Telescopes (APT's) allow an astronomer to be removed form the telescope site in both time and space. APT's 'execute' an observation program (a set of observation requests) expressed in an ASCII-based language (ATIS) and collect observation results expressed in this same language. The observation program is currently constructed by a Principal Astronomer from the requests of multiple users; the execution is currently controlled by a simple heuristic dispatch scheduler. Research aimed at improving the use of APT's is being carried out by the Entropy Reduction Engine (ERE) project at NASA Ames. The overall goal of the ERE project is the study and construction of systems that integrate planning, scheduling, and control. This paper discusses the application of some ERE technical results to the improvement of both the scheduling and the operation of APT's.
The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques.
This paper presents an argument for the appropriateness of Entropy Reduction Engine (ERE) technology to the planning, scheduling, and control components of Automatic Photoelectric Telescope (APT) management. The paper is organized as follows. In the next section, we give a brief summary of the planning and scheduling requirements for APTs. Following this, in section 3, we give an ERE project precis, couched primarily in terms of project objectives. Section 4 gives a sketch of the match-up between problem and technology, and section 5 outlines where we want to go with this work.
The field of astronomy has recently benefited from the availability of space telescopes. The Hubble Space Telescope (HST), for instance, despite its problems, provides a unique and valuable view of the universe. However, unlike HST, a telescope need not be in low Earth orbit to escape our thickening atmosphere: it is currently technologically feasible to put a telescope on the moon, and there are excellent reasons for doing this. Either in low Earth orbit or on the moon, a space telescope represents an expensive and sought-after resource. Thus, the planning, scheduling, and control of these telescopes is an important problem that must be seriously studied.
The objective of multi-use telescopes is to reduce the initial and operational costs of space telescopes to the point where a fair number of telescopes, a dozen or so, would be affordable. The basic approach is to develop a common telescope, control system, and power and communications subsystem that can be used with a wide variety of instrument payloads, i.e., imaging CCD cameras, photometers, spectrographs, etc. By having such a multi-use and multi-user telescope, a common practice for earth-based telescopes, development cost can be shared across many telescopes, and the telescopes can be produced in economical batches.
We compare the utility of different commitment strategies in planning. Under a 'least commitment strategy', plans are represented as partial orders and operators are ordered only when interactions are detected. We investigate claims of the inherent advantages of planning with partial orders, as compared to planning with total orders. By focusing our analysis on the issue of operator ordering commitment, we are able to carry out a rigorous comparative analysis of two planners. We show that partial-order planning can be more efficient than total-order planning, but we also show that this is not necessarily so.
The objective of multi-use telescopes is to reduce the initial and operational costs of space telescopes to the point where a fair number of telescopes, a dozen or so, would be affordable. The basic approach is to develop a common telescope, control system, and power and communications subsystem that can be used with a wide variety of instrument payloads, i.e., imaging CCD cameras, photometers, spectrographs, etc. By having such a multi-use and multi-user telescope, a common practice for earth-based telescopes, development cost can be shared across many telescopes, and the telescopes can be produced in economical batches.
The Entropy Reduction Engine, ERE project, is focusing on the construction of integrated planning and scheduling systems. Specifically, the project is studying the problem of integrating planning and scheduling in the context of the closed loop plan use. The results of this research are particularly relevant when there is some element of dynamism in the environment, and thus some chance that a previously formed plan will fail. After a preliminary study of the APT management and control problem, it was felt that it presents an excellent opportunity to show some of the ERE Project's technical results. Of course, the alignment between technology and problem is not perfect, so planning and scheduling for APTs presents some new and difficult challenges as well.
The Entropy Reduction Engine, an architecture for the integration of planning, scheduling, and control, is described. The architecture is motivated, presented, and analyzed in terms of its different components; namely, problem reduction, temporal projection, and situated control rule execution. Experience with this architecture has motivated the recent integration of learning. The learning methods are described along with their impact on architecture performance.
A projection algorithm is presented for incremental control rule synthesis. The algorithm synthesizes an initial set of goal achieving control rules using a combination of situation probability and estimated remaining work as a search heuristic. This set of control rules has a certain probability of satisfying the given goal. The probability is incrementally increased by synthesizing additional control rules to handle 'error' situations the execution system is likely to encounter when following the initial control rules. By using situation probabilities, the algorithm achieves a computationally effective balance between the limited robustness of triangle tables and the absolute robustness of universal plans.