A vision-language-guided and deep reinforcement learning-enabled approach for unstructured human-robot collaborative manufacturing task fulfilment Article Swipe

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Pai Zheng , Chengxi Li , Junming Fan , Lihui Wang ·

YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.1016/j.cirp.2024.04.003

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Reinforcement Learning

Computer Science

Human–Computer Interaction

Artificial Intelligence

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Reinforcement learning Task (project management) Computer science Human–computer interaction Artificial intelligence Interface (matter) Representation (politics) Robot Task analysis Engineering Systems engineering Parallel computing Politics Political science Law Bubble Maximum bubble pressure method

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Type: article
Language: en
Landing Page: https://doi.org/10.1016/j.cirp.2024.04.003
OA Status: hybrid
Cited By: 34
References: 17
Related Works: 10
OpenAlex ID: https://openalex.org/W4394880521

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OpenAlex ID: https://openalex.org/W4394880521

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DOI: https://doi.org/10.1016/j.cirp.2024.04.003

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Title: A vision-language-guided and deep reinforcement learning-enabled approach for unstructured human-robot collaborative manufacturing task fulfilment

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Type: article

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Language: en

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Publication year: 2024

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Publication date: 2024-01-01

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Authors: Pai Zheng, Chengxi Li, Junming Fan, Lihui Wang

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Landing page: https://doi.org/10.1016/j.cirp.2024.04.003

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OA status: hybrid

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Concepts: Reinforcement learning, Task (project management), Computer science, Human–computer interaction, Artificial intelligence, Interface (matter), Representation (politics), Robot, Task analysis, Engineering, Systems engineering, Parallel computing, Politics, Political science, Law, Bubble, Maximum bubble pressure method

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Cited by: 34

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Citations by year (recent): 2025: 32, 2024: 2

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References (count): 17

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Related works (count): 10

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