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Construction waste recycling robot for nails and screws: Computer vision technology and neural network approach

  • Zeli Wang
  • , Heng Li*
  • , Xiaoling Zhang
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Waste management scene is in urgent need of robotic waste sorter. Nails and screws, as part of the construction waste scene, are hard to be found and can therefore, cause damage to the site's construction safety and increase the material loss. This paper presents a construction waste recycling robot. In order to complete the recycling tasks, robots are expected to inspect the entire working environment and identify the target objects. This research uses neural network technology to assist the robot patrol in an unknown work environment and to use faster R-CNN methods to find scattered nails and screws in real time, so that the robot can automatically recycle nails and screws. This study introduces computer vision technology and a full-coverage path-planning algorithm into the field of construction waste management and proposes a novel construction waste recycling approach. Based on this robot, we can continue our study of construction waste recycling robots that can automatically sort and recycle most construction waste in the future.
Original languageEnglish
Pages (from-to)220-228
JournalAutomation in Construction
Volume97
Online published17 Nov 2018
DOIs
Publication statusPublished - Jan 2019

Funding

We are thankful for the financial support of 1) The Research Grants Council, University Grants Committee of Hong Kong grant entitled “Proactively Monitoring Construction Progress by Integrating 3D Laser-scanning and BIM” ( PolyU 152093/14E ); and 2) Environment and Conservation Fund entitled “Construction Sorting and Recycling Robot” (grant no. ECF 70/2017 ).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Research Keywords

  • Computer vision
  • Construction waste management
  • Faster R-CNN
  • Mobile robot coverage
  • Neural network
  • Robotics in construction sites

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