Frontiers in construction 3D printing: self-monitoring, multi-robot, drone-assisted processes

Abstract To overcome productivity issues and revolutionize the stagnating construction industry, a large amount of research efforts has been devoted to robot-assisted construction technology. The advancements in robotics including mechanical system design, tool design, digital system design, and numerical control systems design enabled engineers to create complex geometries that are infeasible for conventional construction methods. In addition, innovative robotic systems that utilize mobile platforms, multiple robots, and unmanned aerial vehicles have demonstrated significant promise in fully automating the construction process. This work will provide a perspective on the state-of-the-art applications of robotics in the revolution of construction, where a comprehensive review of the current development of the relevant software and hardware, 3D concrete printing (3DCP), robot-assisted assembly of discrete prefabricated blocks, real-time quality monitoring and feedback control systems, and typical innovative robot-assisted structural designs are conducted. Finally, the limitations of existing robot-assisted construction technology are identified, which leads to several recommendations for future research toward fully automatic construction.

Authors

Institutions

Publication Details

Journal
Progress in Additive Manufacturing
Published
2024-10-05
DOI
https://doi.org/10.1007/s40964-024-00794-8
Citations
16
Primary Topic
Innovations in Concrete and Construction Materials
Type
article
Field-Weighted Citation Impact
4.24

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Frontiers in construction 3D printing: self-monitoring, multi-robot, drone-assisted processes

Lü Tian, Phuong Tran, Shuai Li, Hung-Xuan Nguyen
16 citations
Progress in Additive Manufacturing
Innovations in Concrete and Construction Materials
4.24
article

Frontiers in construction 3D printing: self-monitoring, multi-robot, drone-assisted processes

Lü Tian, Phuong Tran, Shuai Li, Hung-Xuan Nguyen
article en
16 citations

Abstract

Abstract To overcome productivity issues and revolutionize the stagnating construction industry, a large amount of research efforts has been devoted to robot-assisted construction technology. The advancements in robotics including mechanical system design, tool design, digital system design, and numerical control systems design enabled engineers to create complex geometries that are infeasible for conventional construction methods. In addition, innovative robotic systems that utilize mobile platforms, multiple robots, and unmanned aerial vehicles have demonstrated significant promise in fully automating the construction process. This work will provide a perspective on the state-of-the-art applications of robotics in the revolution of construction, where a comprehensive review of the current development of the relevant software and hardware, 3D concrete printing (3DCP), robot-assisted assembly of discrete prefabricated blocks, real-time quality monitoring and feedback control systems, and typical innovative robot-assisted structural designs are conducted. Finally, the limitations of existing robot-assisted construction technology are identified, which leads to several recommendations for future research toward fully automatic construction.

Progress in Additive ManufacturingVol. 10(4)
HUTECH University, Ho Chi Minh City University of Technology (VN), RMIT University (AU)
RMIT University
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Innovations in Concrete and Construction Materials
4.24
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.