Automated removal of planar clutter from 3D point clouds for improving industrial object recognition

T. Czerniawski, M. Nahangi, S. Walbridge, C. Haas

Research output: Contribution to conferencePaperpeer-review

Abstract

The industrial construction industry makes use of prefabrication, preassembly, modularization and offsite fabrication (PPMOF) for project execution because they offer a superior level of control as compared to on-site operations. This control is enabled by systematic and thorough performance feedback loops. Improvement of the feedback systems within these facilities will require a transition away from suboptimal manual data collection to more reliable automated data collection and processing. Laser scanners are an effective tool for automatically gathering dimensional data but extraction of useful information from point clouds remains a challenge. The speed of 3D object recognition methods depends on the size of the search space. Methods for reducing this search space are needed in order to improve the performance of 3D object recognition and subsequent information extraction. Large planar objects (e.g. floors and walls) constitute a large portion of the search space in fabrication facilities, yet are rarely the objects of interest for analysis. In this paper, an automated framework for detecting and removing large planes in point clouds is presented to speed up object recognition. The raw point cloud is first Guassian mapped to normal vector space by calculating normal vectors at each point. The Gaussian sphere is clustered using a density-based clustering algorithm and major parallel planes are segmented from the rest of the point cloud. The major planes are removed and the remaining objects in the scene continue on to 3D object recognition. Results show the algorithm for automatic plane removal can reduce the search space for object recognition by as much as 60% or 70%.

Original languageEnglish (US)
Pages357-365
Number of pages9
DOIs
StatePublished - 2016
Externally publishedYes
Event33rd International Symposium on Automation and Robotics in Construction, ISARC 2016 - Auburn, United States
Duration: Jul 18 2016Jul 21 2016

Other

Other33rd International Symposium on Automation and Robotics in Construction, ISARC 2016
CountryUnited States
CityAuburn
Period7/18/167/21/16

Keywords

  • 3D laser scanning
  • 3D object recognition
  • 3D point cloud
  • Clutter removal
  • Fabrication and process control
  • Industrial fabrication
  • Pipe spool

ASJC Scopus subject areas

  • Artificial Intelligence
  • Civil and Structural Engineering
  • Human-Computer Interaction
  • Geotechnical Engineering and Engineering Geology

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