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Proceedings Paper

A Representation for Error Detection and Recovery in Robot Task Plans
Author(s): D. M. Lyons; R. Vijaykumar; S. T. Venkataraman
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Paper Abstract

A flexible robotic assembly cell will have to deal with error detection, diagnosis and recovery. Much of the literature in this area to date has concentrated on devising specific algorithms for detection and recovery, and has largely ignored the central issues of (1) determining what needs to be represented in order to deal with the problem of detecting and recovering from errors and (2) building an appropriate general representation. We begin our work by defining the components of the error detection and recovery problem and by defining what kinds of errors can reasonably be detected. We then construct a generally applicable representation for error detection and recovery information that supports these definitions. The representation, which is based on our previous work on task grammars16, is similar to Donald's3 notation of an EDR plan. We use RS, a process-based model for representing task plans11, as the underlying 'vocabulary' to describe our representation concisely. We evaluate our representation by applying it to the following problems: 1. Distinguishing between planned decision-making and error detection so that the two are not intermixed arbitrarily in a plan. 2. Developing a hierarchical structuring to allow localized error detection and recovery. 3. Gracefully handling errors that cannot be diagnosed. 4. Performing error monitoring on the error monitoring system. Although some formal material is included here, the main emphasis in this paper will be on the representational advantages of our approach.

Paper Details

Date Published: 1 February 1990
PDF: 12 pages
Proc. SPIE 1196, Intelligent Control and Adaptive Systems, (1 February 1990); doi: 10.1117/12.969903
Show Author Affiliations
D. M. Lyons, North American Philips Corporation (United States)
R. Vijaykumar, University of Southern Maine (United States)
S. T. Venkataraman, Jet Propulsion Labs (United States)

Published in SPIE Proceedings Vol. 1196:
Intelligent Control and Adaptive Systems
Guillermo Rodriguez, Editor(s)

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