Human–robot collaboration for on-site construction

Zhang, Ming; Xu, Rui; Wu, Haitao; Pan, Jia; Luo, Xiaowei

doi:10.1016/j.autcon.2023.104812

Cited by 37 publications

(11 citation statements)

References 120 publications

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“… [ 73 ] ML Data mining methodology employing artificial intelligence and a probabilistic approach for energy-efficient structural health monitoring with noisy and delayed signals 2019 Identifying structural damage using binary signals with noise and delay [ 75 ] AI Human–robot collaboration for on-site construction 2023 During the additive manufacturing process, building elements are automatically installed, and printing material is extruded. [ 107 ] ML Robotic technologies for on-site building construction: A systematic review 2020 Advanced robotic applications in construction encompass autonomous assembly, in-situ fabrication, bricklaying, spraying, foam concrete printing, and surface unevenness recognition. [ 72 ] AI On-site autonomous construction robots: Towards unsupervised building 2020 Creating an automated approach for dry-stacking stones to provide foundation support and the efficient assembly of superstructure components.…”

Section: Applications Of Ai and ML In Construction Project Lifecycle ...mentioning

confidence: 99%

Artificial intelligence and machine learning applications in the project lifecycle of the construction industry: A comprehensive review

Datta,

Islam,

Rahman Sobuz

et al. 2024

Heliyon

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Section: Applications Of Ai and ML In Construction Project Lifecycle ...mentioning

confidence: 99%

Artificial intelligence and machine learning applications in the project lifecycle of the construction industry: A comprehensive review

Datta,

Islam,

Rahman Sobuz

et al. 2024

Heliyon

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“…[ 10 ] In construction, collaborative robots execute tasks like excavation and assembly, merging worker expertise with autonomous efficiency. [ 11 ] Agriculture utilizes HRI for targeted crop recognition, aiming to enhance agricultural adaptability and efficiency. [ 12 ] In smart manufacturing, the aim is to integrate AI in a human‐centric way to improve capabilities and create personalized products, a step toward Industry 5.0.…”

Section: Overviewmentioning

confidence: 99%

Multimodal Human–Robot Interaction for Human‐Centric Smart Manufacturing: A Survey

Wang,

Zheng,

et al. 2023

Advanced Intelligent Systems

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Human–robot interaction (HRI) has escalated in notability in recent years, and multimodal communication and control strategies are necessitated to guarantee a secure, efficient, and intelligent HRI experience. In spite of the considerable focus on multimodal HRI, comprehensive disquisitions delineating various modalities and intricately analyzing their combinations remain elusive, consequently limiting holistic understanding and future advancements. This article aspires to bridge this inadequacy by conducting a profound exploration of multimodal HRI, predominantly concentrating on four principal modalities: vision, auditory and language, haptics, and physiological sensing. An extensive review encapsulating algorithmic dissection, interface devices, and applicative dimensions forms part of this discourse. This manuscript distinctively combines multimodal HRI with cognitive science, deeply probing into the three dimensions, perception, cognition, and action, thereby demystifying algorithms intrinsic to multimodal HRI. Finally, it accentuates the empirical challenges and contours preemptive trajectories for multimodal HRI in human‐centric smart manufacturing.

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“…With the shortage of labor and skilled workers, industrialization in the construction industry is a necessary path for future development (Edirisinghe, 2019). Construction robots have overturned the traditional construction system, making construction more efficient, safe and intelligent (Zhang et al , 2023). Construction robots are currently an emerging industry with broad market prospects (Bogue, 2018).…”

Section: Introductionmentioning

confidence: 99%

Research on dual robot collaboration method based on improved double ant colony algorithm

Jia,

Tang,

Zhang

et al. 2024

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Purpose This study aims to propose an efficient dual-robot task collaboration strategy to address the issue of low work efficiency and inability to meet the production needs of a single robot during construction operations. Design/methodology/approach A hybrid task allocation method based on integer programming and auction algorithms, with the aim of achieving a balanced workload between two robots has been proposed. In addition, while ensuring reasonable workload allocation between the two robots, an improved dual ant colony algorithm was used to solve the dual traveling salesman problem, and the global path planning of the two robots was determined, resulting in an efficient and collision-free path for the dual robots to operate. Meanwhile, an improved fast Random tree rapidly-exploring random tree algorithm is introduced as a local obstacle avoidance strategy. Findings The proposed method combines randomization and iteration techniques to achieve an efficient task allocation strategy for two robots, ensuring the relative optimal global path of the two robots in cooperation and solving complex local obstacle avoidance problems. Originality/value This method is applied to the scene of steel bar tying in construction work, with the workload allocation and collaborative work between two robots as evaluation indicators. The experimental results show that this method can efficiently complete the steel bar banding operation, effectively reduce the interference between the two robots and minimize the interference of obstacles in the environment.

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Human–robot collaboration for on-site construction

Cited by 37 publications

References 120 publications

Artificial intelligence and machine learning applications in the project lifecycle of the construction industry: A comprehensive review

Artificial intelligence and machine learning applications in the project lifecycle of the construction industry: A comprehensive review

Multimodal Human–Robot Interaction for Human‐Centric Smart Manufacturing: A Survey

Research on dual robot collaboration method based on improved double ant colony algorithm

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