Towards automatic error recovery in robot programs

Maria Gini, Giuseppina Gini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Unexpected events can cause the failure of apparently "correct" robot programs. The interaction with the real world and its unpredictability make the problem of error recovery in robot programming specially important. The goal of the paper is to present a general framework in which the activity of error recovery can be automated. This is accomplished by introducing a monitor program which identifies the appearance of any error and attempt to correct that error. The correction is done using a knowledge base where the knowledge that the user has about error identification and correction is expressed in symbolic form. An inference mechanism allows extension of this knowledge base for use in complex and unanticipated situations.

Original languageEnglish (US)
Title of host publicationMethods and Tools for Computer Integrated Manufacturing - Advanced CREST Course on Computer Integrated Manufacturing, CIM 83
EditorsU. Rembold, R. Dillmann
PublisherSpringer- Verlag
Pages411-416
Number of pages6
ISBN (Print)9783540129264
DOIs
StatePublished - Jan 1 1984
EventAdvanced Course on Computer Integrated Manufacturing, CIM 1983 - Karlsruhe, Germany
Duration: Sep 5 1983Sep 16 1983

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume168 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherAdvanced Course on Computer Integrated Manufacturing, CIM 1983
CountryGermany
CityKarlsruhe
Period9/5/839/16/83

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    Gini, M., & Gini, G. (1984). Towards automatic error recovery in robot programs. In U. Rembold, & R. Dillmann (Eds.), Methods and Tools for Computer Integrated Manufacturing - Advanced CREST Course on Computer Integrated Manufacturing, CIM 83 (pp. 411-416). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 168 LNCS). Springer- Verlag. https://doi.org/10.1007/BFb0014790