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Robot Floor-Tiling Control Method Based on Finite-State Machine and Visual Measurement in Limited FOV

Author(s): ORCID
ORCID
ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2021
Page(s): 1-16
DOI: 10.1155/2021/8372815
Abstract:

In recent years, accelerative aging society is meeting the short supply of young and middle-aged labor. Particularly, most young people are reluctant to work in the construction industry, which has caused the labor cost of floor tiling to rise year by year. In addition, floor tiling requires workers to continuously bend over or lean over to work, which greatly jeopardizes the physical health of them. Therefore, advanced technology applied in floor tiling is highly demanded to replace the traditional manual method. On the context, the automatic method of floor tiling may promote the transformation and upgrading of the industry. Although a few robots for floor tiling have been developed, the automation of existing systems is still at a low level. This paper proposes a robot floor-tiling control strategy based on visual measurement feedback and finite-state machine, in which the calculation of tile position information in limited field of vision is obtained by an improved Canny edge detection and a Hough linear transformation. Moreover, an algorithm for complementing tile position information based on visual measurement is proposed, and the quality of tile laying is evaluated online. To evaluate the effect of the proposed control strategy, the experimental verifications are given. The experimental results indicate that the proposed method can complete the automatic floor tiling with high accuracy.

Copyright: © Shun Wang et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10630604
  • Published on:
    01/10/2021
  • Last updated on:
    17/02/2022
 
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