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Li L, Yuan P, Tang Y, Cooper G, Thurlbeck S, Cheung CM, Manu P, Yunusa-Kaltungo A, Weightman A. The potential of construction robotics to reduce airborne virus transmission in the construction industry in the UK and China. Heliyon 2024; 10:e29697. [PMID: 38694123 PMCID: PMC11061700 DOI: 10.1016/j.heliyon.2024.e29697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 04/14/2024] [Accepted: 04/14/2024] [Indexed: 05/04/2024] Open
Abstract
This paper aims to identify construction robotics' potential to reduce airborne virus transmission, review factors limiting the technology's adoption and highlight how similar barriers have been addressed in other industries. Construction robotics were identified and classified into 8 themes with 25 categories through a critical literature review. We undertook interviews with 4 construction contractors and conducted an online questionnaire with 32 experts from the UK (n=14) and China (n=18) who reviewed the robotic systems we identified and ranked the potential ability of each to reduce airborne virus transmission within the construction industry. The results of this study showed that construction robotics is not only beneficial to reduce airborne virus transmission, but may also help to reduce the spread of future contagious viruses. We found no significant difference (P>0.05) in practical usage and implementation barriers to construction robotics between the UK and China. Cost, training and limited awareness of robotic technologies were the main implementation barriers we identified in both countries. Both the UK and China may need to adopt strategies such as providing more financial support to small construction industries and skill training which are utilised successfully in other sectors to realise the potential of construction robotic technologies.
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Affiliation(s)
- Lutong Li
- Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester, M13 9PL, United Kingdom
| | - Pu Yuan
- Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester, M13 9PL, United Kingdom
| | - Yuan Tang
- Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester, M13 9PL, United Kingdom
| | - Glen Cooper
- Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester, M13 9PL, United Kingdom
| | - Simon Thurlbeck
- Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester, M13 9PL, United Kingdom
| | - Clara Man Cheung
- Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester, M13 9PL, United Kingdom
| | - Patrick Manu
- School of Architecture and Environment, University of the West of England, Bristol, BS16 1QY, United Kingdom
| | - Akilu Yunusa-Kaltungo
- Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester, M13 9PL, United Kingdom
| | - Andrew Weightman
- Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester, M13 9PL, United Kingdom
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Guan E, Wang Y, Zhang Y, Zhao Y. A novel distributed meta-module motion design for modular robotic systems based on grid partition method. Sci Prog 2024; 107:368504241260176. [PMID: 38850047 PMCID: PMC11162137 DOI: 10.1177/00368504241260176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2024]
Abstract
This article studies a meta-module motion design approach for homogenous modular robotic systems in self-configuration. By utilizing configuration diversity, scalability and unit-substitutability, homogenous modular robotic systems can be a promising approach to life detection and space exploration in the future. Based on the requirements of the potential applications, self-configuration can be considered as the precondition. As similar to swarm robotic systems, the distributed control strategy in which the modular robots are operated in a sequence of motion circles consist of 'detection'- 'decision'- 'execution' is of great significance. However, there is a limitation to the applicability of previously proposed work on the self-configuration topic, due to the fact that the self-configuration strategy execution suffers from the motion constraints of modular robots. In order to solve the problem, we propose a grid partition method that removes the gap between the locomotion of a single modular robot and the reconfiguration of the whole system. Under the analysis of the grid partition, the meta-module motion design is proposed to realize the distributed self-configuration strategy. We simulated the self-configuration in M-Lattice, a two-dimensional homogenous modular robotic system.
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Affiliation(s)
- Enguang Guan
- Logistics Engineering College, Shanghai Maritime University, Shanghai, China
| | - Yao Wang
- Logistics Engineering College, Shanghai Maritime University, Shanghai, China
| | - Yulong Zhang
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yanzheng Zhao
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
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Shu J, Li W, Gao Y. Collision-free trajectory planning for robotic assembly of lightweight structures. AUTOMATION IN CONSTRUCTION 2022; 142:104520. [PMID: 35937900 PMCID: PMC9345853 DOI: 10.1016/j.autcon.2022.104520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 06/30/2022] [Accepted: 07/30/2022] [Indexed: 06/15/2023]
Abstract
This research presents a trajectory planning approach for robotic assembly of lightweight structures for COVID-19 healthcare facilities. The prefabricated building components of COVID-19 healthcare facilities have nonnegligible volume, where the crux of the scientific question lies in how to incorporate geometry-based collision checks in trajectory planning. This research developed an algorithm that refines the RRT* (Rapidly-exploring Random Tree-Star) algorithm to enable the detour of a planned trajectory based on the geometry of prefabricated components to prevent collisions. Testing of the approach reveals that it has satisfactory collision-avoiding and trajectory-smoothing performance, and is time- and labour-saving compared with the traditional human method. The satisfactory results highlight the practical implication of this research, where robots can replace human labour and contribute to the mitigation of COVID-19 spread on construction sites. The subsequent research will investigate the use of a collaborative robot to screw bolt connections after the components are assembled at locations.
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Affiliation(s)
- Jiangpeng Shu
- College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
- Centre for Balance Architecture, Zhejiang University, Hangzhou 310058, China
- The Architectural Design & Research Institute of Zhejiang University Co. Ltd, Hangzhou 310028, China
| | - Wenhao Li
- College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
| | - Yifan Gao
- College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
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Gao Y, Meng J, Shu J, Liu Y. BIM-based task and motion planning prototype for robotic assembly of COVID-19 hospitalisation light weight structures. AUTOMATION IN CONSTRUCTION 2022; 140:104370. [PMID: 35607382 PMCID: PMC9117582 DOI: 10.1016/j.autcon.2022.104370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 04/25/2022] [Accepted: 05/16/2022] [Indexed: 05/13/2023]
Abstract
Fast transmission of COVID-19 led to mass cancelling of events to contain the virus outbreak. Amid lockdown restrictions, a vast number of construction projects came to a halt. Robotic platforms can perform construction projects in an unmanned manner, thus ensuring the essential construction tasks are not suspended during the pandemic. This research developed a BIM-based prototype, including a task planning algorithm and a motion planning algorithm, to assist in the robotic assembly of COVID-19 hospitalisation light weight structures with prefabricated components. The task planning algorithm can determine the assembly sequence and coordinates for various types of prefabricated components. The motion planning algorithm can generate robots' kinematic parameters for performing the assembly of the prefabricated components. Testing of the prototype finds that it has satisfactory performance in terms of 1) the reasonableness of assembly sequence determined, 2) reachability for the assembly coordinates of prefabricated components, and 3) capability to avoid obstacles.
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Affiliation(s)
- Yifan Gao
- College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
- Center for Balance Architecture, Zhejiang University, Hangzhou 310058, China
- The Architectural Design & Research Institute of Zhejiang University Co. Ltd, Hangzhou 310058, China
| | - Jiawei Meng
- Department of Mechanical Engineering, University College London, London WC1E 6BT, United Kingdom
| | - Jiangpeng Shu
- College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
| | - Yuanchang Liu
- Department of Mechanical Engineering, University College London, London WC1E 6BT, United Kingdom
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Leder S, Kim H, Oguz OS, Kubail Kalousdian N, Hartmann VN, Menges A, Toussaint M, Sitti M. Leveraging Building Material as Part of the In-Plane Robotic Kinematic System for Collective Construction. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2022; 9:e2201524. [PMID: 35758558 PMCID: PMC9404414 DOI: 10.1002/advs.202201524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 05/13/2022] [Indexed: 06/15/2023]
Abstract
Although collective robotic construction systems are beginning to showcase how multi-robot systems can contribute to building construction by efficiently building low-cost, sustainable structures, the majority of research utilizes non-structural or highly customized materials. A modular collective robotic construction system based on a robotic actuator, which leverages timber struts for the assembly of architectural artifacts as well as part of the robot body for locomotion is presented. The system is co-designed for in-plane assembly from an architectural, robotic, and computer science perspective in order to integrate the various hardware and software constraints into a single workflow. The system is tested using five representative physical scenarios. These proof-of-concept demonstrations showcase three tasks required for construction assembly: the ability of the system to locomote, dynamically change the topology of connecting robotic actuators and timber struts, and collaborate to transport timber struts. As such, the groundwork for a future autonomous collective robotic construction system that could address collective construction assembly and even further increase the flexibility of on-site construction robots through its modularity is laid.
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Affiliation(s)
- Samuel Leder
- Cluster of Excellence IntCDC: Integrative Computational Design and Construction for ArchitectureUniversity of Stuttgart and Max Planck Institute for Intelligent Systems70569StuttgartGermany
- Institute for Computational Design and ConstructionUniversity of Stuttgart70174StuttgartGermany
| | - HyunGyu Kim
- Cluster of Excellence IntCDC: Integrative Computational Design and Construction for ArchitectureUniversity of Stuttgart and Max Planck Institute for Intelligent Systems70569StuttgartGermany
- Physical Intelligence DepartmentMax Planck Institute for Intelligent Systems70569StuttgartGermany
| | - Ozgur Salih Oguz
- Cluster of Excellence IntCDC: Integrative Computational Design and Construction for ArchitectureUniversity of Stuttgart and Max Planck Institute for Intelligent Systems70569StuttgartGermany
- Learning & Intelligent System LaboratoryTechnical University of Berlin10623BerlinGermany
- Computer Engineering DepartmentBilkent UniversityAnkara06800Turkey
| | - Nicolas Kubail Kalousdian
- Cluster of Excellence IntCDC: Integrative Computational Design and Construction for ArchitectureUniversity of Stuttgart and Max Planck Institute for Intelligent Systems70569StuttgartGermany
- Institute for Computational Design and ConstructionUniversity of Stuttgart70174StuttgartGermany
| | - Valentin Noah Hartmann
- Cluster of Excellence IntCDC: Integrative Computational Design and Construction for ArchitectureUniversity of Stuttgart and Max Planck Institute for Intelligent Systems70569StuttgartGermany
- Learning & Intelligent System LaboratoryTechnical University of Berlin10623BerlinGermany
| | - Achim Menges
- Cluster of Excellence IntCDC: Integrative Computational Design and Construction for ArchitectureUniversity of Stuttgart and Max Planck Institute for Intelligent Systems70569StuttgartGermany
- Institute for Computational Design and ConstructionUniversity of Stuttgart70174StuttgartGermany
| | - Marc Toussaint
- Cluster of Excellence IntCDC: Integrative Computational Design and Construction for ArchitectureUniversity of Stuttgart and Max Planck Institute for Intelligent Systems70569StuttgartGermany
- Learning & Intelligent System LaboratoryTechnical University of Berlin10623BerlinGermany
| | - Metin Sitti
- Cluster of Excellence IntCDC: Integrative Computational Design and Construction for ArchitectureUniversity of Stuttgart and Max Planck Institute for Intelligent Systems70569StuttgartGermany
- Physical Intelligence DepartmentMax Planck Institute for Intelligent Systems70569StuttgartGermany
- Institute for Biomedical EngineeringETH ZurichZurich8092Switzerland
- School of Medicine and College of EngineeringKoç UniversityIstanbul34450Turkey
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Abstract
The robotic arm has emerged as an essential tool for the rapid construction of high-quality buildings due to its ability to repeat instructions, achieve precise positioning and fine operations. The robotic arm can also effectively replace workers to complete building construction under low temperature and short daylight conditions. Thus, it can be forward-looking to construct modular buildings in cold region, but how to realize the construction of modular buildings through human-machine coordination and remote operation is a significant issue. This article discusses the feasibility of robotic arm assembly design methods in the field of architecture by simulating the complete design and construction process of modular buildings. According to parameterized module design, a three-dimensional computer model is transformed into an electronic file that directs the action of the robotic arm to complete assembly via a custom processing program. This article details a theoretical and practical exploration of the construction of modular manipulators and has certain guiding significance for the intelligent design and construction of future buildings.
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Wagner C, Dhanaraj N, Rizzo T, Contreras J, Liang H, Lewin G, Pinciroli C. SMAC: Symbiotic Multi-Agent Construction. IEEE Robot Autom Lett 2021. [DOI: 10.1109/lra.2021.3062812] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Jenett B, Abdel-Rahman A, Cheung K, Gershenfeld N. Material–Robot System for Assembly of Discrete Cellular Structures. IEEE Robot Autom Lett 2019. [DOI: 10.1109/lra.2019.2930486] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Local force cues for strength and stability in a distributed robotic construction system. SWARM INTELLIGENCE 2017. [DOI: 10.1007/s11721-017-0149-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Morphological approach for autonomous and adaptive system: The construction of three-dimensional artificial model based on self-reconfigurable modular agents. Neurocomputing 2015. [DOI: 10.1016/j.neucom.2012.12.082] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Sprowitz A, Pouya S, Bonardi S, Van Den Kieboom J, Mockel R, Billard A, Dillenbourg P, Jan Ijspeert A. Roombots: Reconfigurable Robots for Adaptive Furniture. IEEE COMPUT INTELL M 2010. [DOI: 10.1109/mci.2010.937320] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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