What question did this study set out to answer?

To systematically map and synthesize the fragmented research landscape of Physical Artificial Intelligence through a data-driven computational literature review.

September 18, 2026TechnologiesOpen Access

Physical AI: A Data-Driven Survey of Foundations, Technologies, and Applications

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Authors

JSJohannes StübingerCoburg University of Applied Sciences FMFabio MetzCoburg University of Applied Sciences

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Implication

Systematic review uncovers five core research clusters in physical AI literature, highlighting operational challenges and thematic fragmentation facing trustworthy autonomous systems.

Key Points

To systematically map and synthesize the fragmented research landscape of Physical Artificial Intelligence through a data-driven computational literature review.
Sampled the top 100 Google Scholar publications indexed under the search terms “Physical Artificial Intelligence” and “Physical AI”.
Applied an AI-assisted computational analysis pipeline utilizing a Large Language Model via a Python-based API to execute structured thematic categorization.
Categorized the literature into five distinct data-driven clusters: Sensor Infrastructure and Architectures, Core Learning and Modeling Methodologies, Sim-to-Real and Digital Twins, Applications, and Safety, Governance, and Ethics.
Identified critical operational challenges and substantial disciplinary fragmentation across current Physical AI research that impede the development of trustworthy autonomous systems.

Cite This Study

Stübinger et al. (2026) studied this question.

synapsesocial.com/papers/6aad0b86de0393d728b89cfe https://doi.org/10.3390/technologies14090588

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Implication

Systematic review uncovers five core research clusters in physical AI literature, highlighting operational challenges and thematic fragmentation facing trustworthy autonomous systems.

Physical AI: A Data-Driven Survey of Foundations, Technologies, and Applications

Discussion

Member takes

Implication

Key Points

Cite This Study

Physical AI: A Data-Driven Survey of Foundations, Technologies, and Applications

Discussion

Member takes

Implication

Key Points

Cite This Study

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