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- Publisher Website: 10.1016/j.jenvman.2023.119341
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Article: Augmented reality-enabled human-robot collaboration to balance construction waste sorting efficiency and occupational safety and health
| Title | Augmented reality-enabled human-robot collaboration to balance construction waste sorting efficiency and occupational safety and health |
|---|---|
| Authors | |
| Keywords | Augmented reality (AR) Automated waste sorting Construction and demolition waste Human-robot collaboration (HRC) Occupational safety and health (OSH) |
| Issue Date | 30-Nov-2023 |
| Publisher | Elsevier |
| Citation | Journal of Environmental Management, 2023, v. 348 How to Cite? |
| Abstract | Construction waste sorting (CWS) is highly recommended as a key step for construction waste management. However, current CWS involves humans’ manual hand-picking, which poses significant threats to their occupational safety and health (OSH). Robotic sorting promises to change the situation by adopting modern artificial intelligence and automation technologies. However, in practice, it is usually challenging for robots to do an efficient job (e.g., measured by quickness and accuracy) owing to the difficulties in precisely recognizing compositions of the mixed and heterogeneous waste stream. Leveraging augmented reality (AR) as a communication interface, this research aims to develop a human-robot collaboration (HRC) approach to address the dilemmatic balance between CWS efficiency and OSH. Firstly, a model for human-robot collaborative sorting using AR is established. Then, a prototype for the AR-enable collaborative sorting system is developed and evaluated. The experimental results demonstrate that the proposed AR-enabled HRC method can improve the accuracy rate of CWS by 10% and 15% for sorting isolated waste and obscured waste, respectively, when compared to the method without human involvement. Interview results indicate a significant improvement in OSH, especially the reduction of contamination risks and machinery risks. The research lays out a human-robot collaborative paradigm for productive and safe CWS via an immersive and interactive interface like AR. |
| Persistent Identifier | http://hdl.handle.net/10722/339595 |
| ISSN | 2023 Impact Factor: 8.0 2023 SCImago Journal Rankings: 1.771 |
| ISI Accession Number ID |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Lu, Weisheng Wilson | - |
| dc.contributor.author | Chen, Junjie | - |
| dc.contributor.author | FU, Yonglin | - |
| dc.contributor.author | PAN, Yipeng | - |
| dc.date.accessioned | 2024-03-11T10:37:52Z | - |
| dc.date.available | 2024-03-11T10:37:52Z | - |
| dc.date.issued | 2023-11-30 | - |
| dc.identifier.citation | Journal of Environmental Management, 2023, v. 348 | - |
| dc.identifier.issn | 0301-4797 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/339595 | - |
| dc.description.abstract | <p>Construction waste sorting (CWS) is highly recommended as a key step for construction <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/waste-management" title="Learn more about waste management from ScienceDirect's AI-generated Topic Pages">waste management</a>. However, current CWS involves humans’ manual hand-picking, which poses significant threats to their occupational safety and health (OSH). Robotic sorting promises to change the situation by adopting modern artificial intelligence and automation <a href="https://www.sciencedirect.com/topics/earth-and-planetary-sciences/science-and-technology" title="Learn more about technologies from ScienceDirect's AI-generated Topic Pages">technologies</a>. However, in practice, it is usually challenging for robots to do an efficient job (e.g., measured by quickness and accuracy) owing to the difficulties in precisely recognizing compositions of the mixed and heterogeneous waste stream. Leveraging <a href="https://www.sciencedirect.com/topics/engineering/augmented-reality" title="Learn more about augmented reality from ScienceDirect's AI-generated Topic Pages">augmented reality</a> (AR) as a communication interface, this research aims to develop a human-robot collaboration (HRC) approach to address the dilemmatic balance between CWS efficiency and OSH. Firstly, a model for human-robot collaborative sorting using AR is established. Then, a prototype for the AR-enable collaborative sorting system is developed and evaluated. The experimental results demonstrate that the proposed AR-enabled HRC method can improve the accuracy rate of CWS by 10% and 15% for sorting isolated waste and obscured waste, respectively, when compared to the method without human involvement. Interview results indicate a significant improvement in OSH, especially the reduction of contamination risks and machinery risks. The research lays out a human-robot collaborative paradigm for productive and safe CWS via an immersive and interactive interface like AR.<br></p> | - |
| dc.language | eng | - |
| dc.publisher | Elsevier | - |
| dc.relation.ispartof | Journal of Environmental Management | - |
| dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
| dc.subject | Augmented reality (AR) | - |
| dc.subject | Automated waste sorting | - |
| dc.subject | Construction and demolition waste | - |
| dc.subject | Human-robot collaboration (HRC) | - |
| dc.subject | Occupational safety and health (OSH) | - |
| dc.title | Augmented reality-enabled human-robot collaboration to balance construction waste sorting efficiency and occupational safety and health | - |
| dc.type | Article | - |
| dc.identifier.doi | 10.1016/j.jenvman.2023.119341 | - |
| dc.identifier.scopus | eid_2-s2.0-85174199523 | - |
| dc.identifier.volume | 348 | - |
| dc.identifier.isi | WOS:001105806000001 | - |
| dc.identifier.issnl | 0301-4797 | - |