IFC-BASED GENERATION OF SEMANTIC OBSTACLE MAPS FOR AUTONOMOUS ROBOTIC SYSTEMS

Muhammad Anas Gopee, Samuel A. Prieto, Borja García de Soto

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

Abstract

Autonomous Robotic Systems (ARSs) in the construction industry usually have to perform preliminary mapping of construction environments before deployment. For large and complex sites, this can be unpractical and time-consuming, making the avoidance of preliminary mapping a motivation for this study. With Building Information Modeling (BIM), a lot of information is already available about sites. This study proposes a method to make that information available to ARSs to streamline autonomous tasks and remove the need for mapping. This is achieved by automatically generating semantic and color-coded obstacle maps from IFC files. The results are obstacle maps that can be used for autonomous navigation that remove the need for preliminary mapping.

Original languageEnglish (US)
Title of host publicationProceedings of the 2022 European Conference on Computing in Construction
EditorsLavinia Chiara Tagliabue, Daniel M. Hall, Ranjith Soman, Athanasios Chassiakos, Dragana Nikolic
PublisherEuropean Council on Computing in Construction (EC3)
Pages176-183
Number of pages8
ISBN (Print)9788875902261
DOIs
StatePublished - 2022
EventEuropean Conference on Computing in Construction, EC3 2022 - Rhodes, Greece
Duration: Jul 24 2022Jul 26 2022

Publication series

NameProceedings of the European Conference on Computing in Construction
ISSN (Electronic)2684-1150

Conference

ConferenceEuropean Conference on Computing in Construction, EC3 2022
Country/TerritoryGreece
CityRhodes
Period7/24/227/26/22

ASJC Scopus subject areas

  • Information Systems
  • Building and Construction

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