Deep Reinforcement Learning for Prefab Assembly Planning in Robot-based Prefabricated Construction

Zhu, Aiyu; Xu, Gangyan; Pauwels, Pieter; Vries, Bauke de; Fang, Meng

doi:10.1109/case49439.2021.9551402

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Robot-based construction assembly refers to the use of robotic systems for joining together various building components, materials, and systems to form a complete structure or a part of a structure [1]. It has emerged as a promising solution to address various challenges including increasing costs, labor shortages, project schedules, and the increasing demand for safe and efficient construction processes [2]. The use of robotic systems and the corresponding changes to the existing construction workflow are expected to significantly enhance productivity, reduce construction costs, and improve safety of construction projects [3].…”

Section: Introductionmentioning

confidence: 99%

Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT

Hengxu

Zhou

et al. 2023

Buildings

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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.

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Section: Introductionmentioning

confidence: 99%

Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT

Hengxu

Zhou

et al. 2023

Buildings

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Evaluate the Digitalization Degree of Prefabricated Construction Industry in China

2022

2022 7th International Conference on Information and Network Technologies (ICINT)

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Deep Reinforcement Learning for Real-Time Assembly Planning in Robot-Based Prefabricated Construction

Zhu

Dai

et al. 2023

IEEE Trans. Automat. Sci. Eng.

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show abstract

Deep Reinforcement Learning for Prefab Assembly Planning in Robot-based Prefabricated Construction

Cited by 3 publications

References 12 publications

Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT

Robot-Enabled Construction Assembly with Automated Sequence Planning Based on ChatGPT: RoboGPT

Evaluate the Digitalization Degree of Prefabricated Construction Industry in China

Deep Reinforcement Learning for Real-Time Assembly Planning in Robot-Based Prefabricated Construction

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