Bibliometric and Visual Analysis of Deep-Sea Unmanned Underwater Vehicle Literature Based on CiteSpace

This study employs CiteSpace to conduct a visual analysis of Chinese and English literature on deep-sea unmanned underwater vehicles (UUVs), aiming to sort out the research focuses and evolutionary trends in the field of deep-sea UUV research. Literature data related to deep-sea UUVs were collected from the core databases of CNKI (China National Knowledge Infrastructure) and Web of Science (WOS) covering the period from 2019 to 2023. CiteSpace was then used for data processing, collaborative network analysis, and keyword analysis. A total of 1,083 Chinese literature articles and 661 English literature articles were included in the study, with the analysis covering aspects such as publication volume, author collaboration networks, institutional collaboration networks, and keywords. The results show that the annual publication volume presents an overall upward trend, indicating a continuous increase in research enthusiasm for deep-sea UUVs, with domestic research enthusiasm being higher than that of international research. The author collaboration network reveals that the main contributors to deep-sea UUV research are researchers from Chinese universities and research institutes. The key research institutions include Harbin Engineering University, the Chinese Academy of Sciences, and Northwestern Polytechnical University, among others. Research hotspots are expanding from traditional basic technical support to directions such as multi-equipment collaborative operations and adaptation to complex scenarios. Through visual analysis, this study identifies the research focuses and development trends in this field, providing certain theoretical references and data support for subsequent in-depth research in the field.