Mutual-cognition for proactive human–robot collaboration: A mixed reality-enabled visual reasoning-based method Article Swipe
Shufei Li
,
Yingchao You
,
Pai Zheng
,
Xi Vincent Wang
,
Lihui Wang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1080/24725854.2024.2313647
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1080/24725854.2024.2313647
Human-Robot Collaboration (HRC) is key to achieving the flexible automation required by the mass personalization trend, especially towards human-centric intelligent manufacturing. Nevertheless, existing HRC systems suffer from poor task understanding and poor ergonomic satisfaction, which impede empathetic teamwork skills in task execution. To overcome the bottleneck, a Mixed Reality (MR) and visual reasoning-based method is proposed in this research, providing mutual-cognitive task assignment for human and robotic agents’ operations. Firstly, an MR-enabled mutual-cognitive HRC architecture is proposed, with the characteristic of monitoring Digital Twins states, reasoning co-working strategies, and providing cognitive services. Secondly, a visual reasoning approach is introduced, which learns scene interpretation from the visual perception of each agent’s actions and environmental changes to make task planning strategies satisfying human–robot operation needs. Lastly, a safe, ergonomic, and proactive robot motion planning algorithm is proposed to let a robot execute generated co-working strategies, while a human operator is supported with intuitive task operation guidance in the MR environment, achieving empathetic collaboration. Through a demonstration of a disassembly task of aging Electric Vehicle Batteries, the experimental result facilitates cognitive intelligence in Proactive HRC for flexible automation.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1080/24725854.2024.2313647
- OA Status
- hybrid
- Cited By
- 20
- References
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- Related Works
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4391556479Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1080/24725854.2024.2313647Digital Object Identifier
- Title
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Mutual-cognition for proactive human–robot collaboration: A mixed reality-enabled visual reasoning-based methodWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-02-05Full publication date if available
- Authors
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Shufei Li, Yingchao You, Pai Zheng, Xi Vincent Wang, Lihui WangList of authors in order
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https://doi.org/10.1080/24725854.2024.2313647Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1080/24725854.2024.2313647Direct OA link when available
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Human–computer interaction, Cognition, Computer science, Human–robot interaction, Mixed reality, Robot, Augmented reality, Cognitive science, Psychology, Artificial intelligence, NeuroscienceTop concepts (fields/topics) attached by OpenAlex
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20Total citation count in OpenAlex
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2025: 18, 2024: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| publication_date | 2024-02-05 |
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