A framework for real-time pro-active safety assistance for mobile crane lifting operations

Yihai Fang, Yong K. Cho, Jingdao Chen

Research output: Contribution to journalArticleResearchpeer-review

54 Citations (Scopus)

Abstract

Despite many safety considerations addressed in lift pre-planning, the ability to provide real-time safety assistance to crane operators and to mitigate human errors during the lifting operation is missing. This research developed a framework for real-time pro-active safety assistance for mobile crane lifting operations. First, crane poses are reconstructed in real-time based on the critical motions of crane parts captured by a sensor system. Second, as-is lift site conditions are automatically modeled and updated based on point cloud data. Lastly, the risk of colliding the crane parts and lifted load into nearby obstructions is pro-actively analyzed and warnings are provided to the operator through a graphical user interface. A prototype system was developed based on the framework and deployed on a mobile crane. Field test results indicate that the system can accurately reconstruct crane motion in real-time and provide pro-active warnings that allow the operator to make timely decisions to mitigate the risk.

Original languageEnglish
Pages (from-to)367-379
Number of pages13
JournalAutomation in Construction
Volume72
DOIs
Publication statusPublished - 1 Dec 2016
Externally publishedYes

Keywords

  • 3D reconstruction
  • Collision hazard analysis
  • Crane motion capturing
  • Crane safety
  • Human error
  • Point cloud
  • Real-time

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