Assessment of Convolutional Neural Networks for Asset Detection in Dynamic Automation Construction Environments

Robert Guamán-Rivera, Oswaldo Menéndez, Tito Arevalo-Ramirez, Katherine Aro, Alvaro Prado, Rodrigo García-Alvarado, Fernando Auat-Cheein

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Integrating social robotics into the construction industry, particularly in the context of Industry 5.0, faces several challenges in creating complex environments that seamlessly blend human and machine interactions. In this regard, the emergence of intelligent and expert systems holds promising technologies to enhance construction tasks focused on robots and workers in 3D printing applications. This work compares several methods of convolutional neural network-based object detectors designed to identify distinct construction assets and workers within the dynamic environment of 3D printing. To this end, different versions of the You Only Look Once v8 (YOLO v8) algorithm have been implemented, trained, and experimentally tested using several images captured within dynamic construction environments. Furthermore, we present an in-depth comparison between YOLO v8 and its preceding versions, namely YOLO v7 and YOLO v5. Experimental results disclosed the high performance of the proposed approach in effectively detecting three distinct entities (workers, robotic platforms, and building elements), achieving a precision rate of up to 98.8%.
Original languageEnglish
Title of host publication2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)
PublisherIEEE
ISBN (Electronic)9798350369533
DOIs
Publication statusPublished - 15 Feb 2024
EventIEEE ChileCon 2023 - Valdivia, Chile
Duration: 5 Dec 20237 Dec 2023

Conference

ConferenceIEEE ChileCon 2023
Country/TerritoryChile
CityValdivia
Period5/12/237/12/23

Keywords

  • 3D printing
  • Automation in construction
  • convolutional neural network
  • robotics

ASJC Scopus subject areas

  • Information Systems and Management
  • Artificial Intelligence
  • Control and Optimization
  • Information Systems
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Hardware and Architecture
  • Computer Networks and Communications

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