Detection of screws on metal-ceiling structures for dismantling tasks in buildings

S. Rolando Cruz-Ramírez, Yasushi Mae, Tomohito Takubo, Tatsuo Arai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Citations (Scopus)

Abstract

In the renewal process of office interiors, a robotic system is needed in order to assist the human workers engaged in this kind of job. Regarding the items in the ceiling side, after the dismantling task of the ceiling panels, it is necessary to remove carefully the screws that once held these boards to the Light Gauge Steel (LGS), with the purpose of reusing. The proposed methodology to achieve the task consists at first of the LGS detection. Such detection is useful as a first approach to detect the screws because a trajectory under and near of that metal-ceiling structure can be generated for a scanning process. In both tasks, a stereo camera configured as an eye-in-hand system is necessary. During the motion under the structure, the screws are detected by applying a multi-template matching process to every caught image. A multi-frame integration increases the robustness in the screw detection process. The results of all the processed images along the trajectory are analyzed in order to measure both the true and the false positive detection rates of the screws attached to the LGS and to measure the 3D position of each one.

Original languageEnglish
Title of host publication2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
Pages4123-4129
Number of pages7
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS - Nice, France
Duration: 22 Sept 200826 Sept 2008

Publication series

Name2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS

Conference

Conference2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS
Country/TerritoryFrance
CityNice
Period22/09/0826/09/08

Keywords

  • Dismantling
  • Human-robot collaboration
  • LGS and screw detection
  • Vision

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