Real-time object recognition and modeling for heavy-equipment operation

Hyojoo Son, Changwan Kim, Hyoungkwan Kim, Kwang Nam Choi, Jeong Min Jee

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

6 Citations (Scopus)

Abstract

Recognition of free-form objects located in environments that are difficult to characterize or are constantly changing is critical in providing interactive background information for construction worksite modeling. It also allows for accurate, efficient, and autonomous operation of heavy equipment in a broad range of construction tasks. This paper presents a realtime process for 3D modeling of a construction worksite scene and focuses on modeling of the target object via flash LADAR, which could be applied to autonomous heavy-equipment operation. The proposed method consists of three steps: noise reduction, object extraction, and 3D model generation. The whole process is fully automatic and is performed in nearly real time. The method was validated in field experiments with actual construction objects. The results show that the proposed method effectively recognizes construction objects, which could be used to enhance efficiency and productivity in the autonomous operation of heavy equipment.

Original languageEnglish
Title of host publicationISARC 2008 - Proceedings from the 25th International Symposium on Automation and Robotics in Construction
PublisherVilnius Gediminas Technical University
Pages232-237
Number of pages6
ISBN (Print)9789955283294
DOIs
Publication statusPublished - 2008
Event25th International Symposium on Automation and Robotics in Construction, ISARC 2008 - Vilnius, Lithuania
Duration: 2008 Jun 262008 Jun 29

Publication series

NameISARC 2008 - Proceedings from the 25th International Symposium on Automation and Robotics in Construction

Other

Other25th International Symposium on Automation and Robotics in Construction, ISARC 2008
Country/TerritoryLithuania
CityVilnius
Period08/6/2608/6/29

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Building and Construction

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