Embodied AI: A Foundation for Intelligent and Autonomous Manufacturing

Embodied artificial intelligence (AI) represents a paradigm shift in the design and construction of intelligent physical systems, where emphasis is placed on the integration of physical interaction and situational awareness of such systems to facilitate adaptive decision-making. This embodiment is realized through an interplay of sensing, control, and actuation, where AI not only interprets data but directly interacts with physical processes. Enabled by advances in deep learning (DL), sensing technologies, and computational infrastructure, embodied AI systems permit new avenues for a broad range of manufacturing applications by building upon a series of transformative capabilities that span semantic data inference, learning-based control, and generative optimization of actuation hardware design. This paper presents an overview of recent advances to enable embodied AI for manufacturing and outlines promising research directions.

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Publication Details

Journal
Engineering
Published
2025-12-01
DOI
https://doi.org/10.1016/j.eng.2025.12.026
Citations
1
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.67
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article

Embodied AI: A Foundation for Intelligent and Autonomous Manufacturing

Robert X. Gao, Jianjing Zhang, Lihui Wang
1 citations
Engineering
Advanced Sensor and Energy Harvesting Materials
0.67
article

Embodied AI: A Foundation for Intelligent and Autonomous Manufacturing

Robert X. Gao, Jianjing Zhang, Lihui Wang
article en
1 citations

Abstract

Embodied artificial intelligence (AI) represents a paradigm shift in the design and construction of intelligent physical systems, where emphasis is placed on the integration of physical interaction and situational awareness of such systems to facilitate adaptive decision-making. This embodiment is realized through an interplay of sensing, control, and actuation, where AI not only interprets data but directly interacts with physical processes. Enabled by advances in deep learning (DL), sensing technologies, and computational infrastructure, embodied AI systems permit new avenues for a broad range of manufacturing applications by building upon a series of transformative capabilities that span semantic data inference, learning-based control, and generative optimization of actuation hardware design. This paper presents an overview of recent advances to enable embodied AI for manufacturing and outlines promising research directions.

Engineering
Case Western Reserve University (US), KTH Royal Institute of Technology (SE)
Industry, innovation and infrastructure
Openalex Percentile: Top 23%
Advanced Sensor and Energy Harvesting Materials
0.67
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