Embodied AI in industrial operations: A systematic literature review

Embodied Artificial Intelligence (EAI) is increasingly seen as a promising route toward flexible automation, also in industrial operations. Yet the term is used inconsistently, and existing surveys often address isolated components rather than the combined role of embodiment, learning, perception, action, data, and industrial deployment constraints. This paper presents a PRISMA-guided systematic literature review of recent EAI research in industrial operations. We first consolidate the terminology of EAI and define four guiding characteristics: embodiment, learning, perception-action coupling, and situated intelligence. Based on this framework, we introduce a manipulation-mobility matrix for classifying physical embodiments and analyze the reviewed literature across industrial applications, research focuses, hardware forms, input and output modalities, learning architectures, datasets, simulation environments, and training paradigms. The results show that current research is dominated by assembly and manufacturing scenarios, stationary robotic arms, vision- and language-based interfaces, and modular foundation model-centered architectures. However, tightly coupled sensorimotor learning, tactile and force feedback, situated intelligence, and validated real-world deployment remain limited. This review clarifies the current state of industrial EAI and identifies the key gaps that must be closed to enable scalable deployment in industrial operations.
Conducts a PRISMA-guided review of 42 recent Embodied AI (EAI) industrial studies. Defines formal industrial EAI terminology via four key characteristics. Proposes a manipulation-mobility matrix classifying robotic embodiments. Finds a dominant focus on stationary cobots and vision/language inputs. Highlights key deployment bottlenecks: decoupled foundation models, precision limits

Subjects

Embodied AI

Structured literature review

Industrial robotics

Foundation models

Human–robot collaboration

Manufacturing

DDC Class

006.3: Artificial Intelligence

629.892: Robot

Lizenz

https://creativecommons.org/licenses/by/4.0/

Publication version

publishedVersion

Dateiname

main.pdf

Typ

Main Article

Größe

3.71 MB

Format

Adobe PDF

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Embodied AI in industrial operations: A systematic literature review