A review on large language models for industrial embodied intelligence

Embodied intelligence (EI) is the latest paradigm in the evolution of artificial intelligence (AI), which becomes a key enabler for advancing intelligent manufacturing in industrial scenarios. In recent years, the explosive growth of large language models (LLMs) has provided a critical pathway for realizing EI, rapidly spawning numerous groundbreaking applications. The widely application of industrial robots is the core characteristics of intelligent manufacturing, where the emergence of EI makes industrial robots becoming smarter and smarter with the capability of executing ever more complex tasks today. Consequently, research on LLMs for industrial EI has rapidly attracted attention from researchers worldwide in the past few years. To better understand the current situation in this field, this paper reviews the progress of LLMs towards industrial EI and discusses the corresponding research status and development trend from the perspectives of the capability breakthrough of single-modal LLMs, the fusion enhancement of multimodal large language models (MLLMs), and the embodiment realization of LLMs. This review aims to provide useful references for the further advancement of LLMs to support the development of industrial EI.