Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT
Robot-based assembly in construction has emerged as a promising solution to address numerous challenges such as increasing costs, labor shortages, and the demand for safe and efficient construction processes. One of the main obstacles in realizing the full potential of these robotic systems is the n...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Buildings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-5309/13/7/1772 |
| _version_ | 1797589983972818944 |
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| author | Hengxu You Yang Ye Tianyu Zhou Qi Zhu Jing Du |
| author_facet | Hengxu You Yang Ye Tianyu Zhou Qi Zhu Jing Du |
| author_sort | Hengxu You |
| collection | DOAJ |
| description | Robot-based assembly in construction has emerged as a promising solution to address numerous challenges such as increasing costs, labor shortages, and the demand for safe and efficient construction processes. One of the main obstacles in realizing the full potential of these robotic systems is the need for effective and efficient sequence planning for construction tasks. Current approaches, including mathematical and heuristic techniques or machine learning methods, face limitations in their adaptability and scalability to dynamic construction environments. To expand the current robot system’s sequential understanding ability, this paper introduces RoboGPT, a novel system that leverages the advanced reasoning capabilities of ChatGPT, a large language model, for automated sequence planning in robot-based assembly applied to construction tasks. The proposed system adapts ChatGPT for construction sequence planning and demonstrates its feasibility and effectiveness through experimental evaluation including two case studies and 80 trials involving real construction tasks. The results show that RoboGPT-driven robots can handle complex construction operations and adapt to changes on the fly. This paper contributes to the ongoing efforts to enhance the capabilities and performance of robot-based assembly systems in the construction industry, and it paves the way for further integration of large language model technologies in the field of construction robotics. |
| first_indexed | 2024-03-11T01:13:54Z |
| format | Article |
| id | doaj.art-b95a60df71f042d186af2f79e3881f8e |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-11T01:13:54Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-b95a60df71f042d186af2f79e3881f8e2023-11-18T18:38:42ZengMDPI AGBuildings2075-53092023-07-01137177210.3390/buildings13071772Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPTHengxu You0Yang Ye1Tianyu Zhou2Qi Zhu3Jing Du4Engineering School of Sustainable Infrastructure & Environment, University of Florida, Gainesville, FL 32611, USAEngineering School of Sustainable Infrastructure & Environment, University of Florida, Gainesville, FL 32611, USAEngineering School of Sustainable Infrastructure & Environment, University of Florida, Gainesville, FL 32611, USAEngineering School of Sustainable Infrastructure & Environment, University of Florida, Gainesville, FL 32611, USAEngineering School of Sustainable Infrastructure & Environment, University of Florida, Gainesville, FL 32611, USARobot-based assembly in construction has emerged as a promising solution to address numerous challenges such as increasing costs, labor shortages, and the demand for safe and efficient construction processes. One of the main obstacles in realizing the full potential of these robotic systems is the need for effective and efficient sequence planning for construction tasks. Current approaches, including mathematical and heuristic techniques or machine learning methods, face limitations in their adaptability and scalability to dynamic construction environments. To expand the current robot system’s sequential understanding ability, this paper introduces RoboGPT, a novel system that leverages the advanced reasoning capabilities of ChatGPT, a large language model, for automated sequence planning in robot-based assembly applied to construction tasks. The proposed system adapts ChatGPT for construction sequence planning and demonstrates its feasibility and effectiveness through experimental evaluation including two case studies and 80 trials involving real construction tasks. The results show that RoboGPT-driven robots can handle complex construction operations and adapt to changes on the fly. This paper contributes to the ongoing efforts to enhance the capabilities and performance of robot-based assembly systems in the construction industry, and it paves the way for further integration of large language model technologies in the field of construction robotics.https://www.mdpi.com/2075-5309/13/7/1772robot-assemblysequential learningChatGPT |
| spellingShingle | Hengxu You Yang Ye Tianyu Zhou Qi Zhu Jing Du Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT Buildings robot-assembly sequential learning ChatGPT |
| title | Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT |
| title_full | Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT |
| title_fullStr | Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT |
| title_full_unstemmed | Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT |
| title_short | Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT |
| title_sort | robot enabled construction assembly with automated sequence planning based on chatgpt robogpt |
| topic | robot-assembly sequential learning ChatGPT |
| url | https://www.mdpi.com/2075-5309/13/7/1772 |
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