Key technologies and applications of embodied artificial intelligence in industrial robot operations

Embodied Artificial Intelligent Industrial Robots (EAI-IR), characterized by capabilities of autonomous perception, dynamic decision-making, and continuous learning, are driving transformation of industrial robots from rigid automation to autonomous intelligent operation, thereby providing critical support for flexible and intelligent transformation of China's manufacturing industry. However, for typical applications such as assembly, grinding, welding, spraying, material handling, and sorting, the closed-loop "perception-decision-action-feedback" mechanism of EAI-IR remains underexplored. Moreover, common key technologies and specific operational technologies across different applications have not been clearly defined, which hinders large-scale deployments of EAI-IR. To address these issues, the key technologies and typical applications of EAI-IR were systematically investigated. A comprehensive review of the current technological landscape was presented, and core bottlenecks were identified. A closed-loop technological framework of "perception-decision-action-feedback" adaptable to different industrial applications was developed, accompanied by an illustration of collaborative interaction mechanisms among its modules. On this basis, five common key technologies: embodied perception, embodied representation, embodied decision-making, embodied control, and embodied evolution were analyzed in depth. Furthermore, application-specific operational technologies for assembly, grinding, welding, spraying, material handling and sorting were summarized. Case studies were then provided to verify the effectiveness and applicability of the proposed technological framework. Finally, core challenges and future trends in the development of embodied AI industrial robot operation technologies were discussed.