Exploration of embodied intelligence and large language models indicates promising pathways for innovative applications.
Embodied intelligence (EI) generates intelligent behaviors through interactions between the body and the environment but exhibits deficiencies in areas such as semantic understanding. In contrast, large language models (LLMs) possess powerful language processing capabilities. Integrating the two can enable a unified system that combines perception, cognition, and decision-making. This article first introduces the concepts, challenges, and recent breakthroughs in EI. It then analyzes the origin, core technologies, and research progress of LLMs. Subsequently, it explores the integration pathways and application scenarios of combining the two paradigms. Finally, the paper highlights ongoing challenges, such as the need for high-quality data and standardized benchmark environments, and underscores the importance of cross-industry collaboration as well as partnerships between academia and industry. The integration of EI and large language models represents a promising direction for the development of general artificial intelligence and is expected to drive innovative applications of intelligent systems across diverse domains.
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Yuan et al. (2025) studied this question.
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