## 3 Analysis and Results
### Visualization Analysis of Keywords
The development of robot technology (e.g., mechanical design, sensor technologies, AI) will closely align with automation and system optimization in the construction process, driving the digital and intelligent transformation of the construction industry. As the research deepens, keywords such as \"human-robot collaboration\", \"automation\", and \"design\" indicate that the field is moving towards greater intelligence and integration, gradually incorporating more interdisciplinary \begin{table}
\begin{tabular}{c l l l} \hline
**No.** & **Keyword** & **Count** & **Centrality** \\ \hline
1 & construction robot & 34 & 0.38 \\
2 & construction robotics & 33 & 0.27 \\
3 & system & 31 & 0.27 \\
4 & construction robots & 21 & 0.19 \\
5 & poverty & 17 & 0.17 \\
5 & design & 17 & 0.14 \\
7 & automation & 16 & 0.12 \\
8 & human–robot collaboration & 13 & 0.12 \\
9 & model & 12 & 0.08 \\ \hline \end{tabular}
\end{table} 
Table 6: Top 9 high-frequency keywords in the research. technologies. The ability to improve human-robot collaboration, enhancing efficiency while ensuring construction safety, will be a key direction for the further development of construction robotics technology. Although \"poverty\" appears less frequently, it still reveals the social impact of construction robotics, especially in enhancing construction efficiency and improving living conditions in impoverished regions. (2) Keyword Clustering  
As shown in Figure 6, it is clear that the research topics in construction robotics are diverse and strongly interconnected. Below is an analysis of the main clusters, discussing the key themes and development trends in the field, in conjunction with current international academic research [23]. Cluster 0 focuses on construction robots and construction robotics. The keywords include \"construction robot\", \"robotic transport mechanism\", \"automated construction\", and \"force feedback\". This cluster centers on the fundamental concepts and applications of construction robots. The research emphasizes how robotics technology is applied in construction tasks, such as transportation and automation. It highlights the design of robotic hardware, automation control, and the enhancement of robots' performance in construction environments. Cluster 1 revolves around simultaneous localization and mapping (SLAM), with keywords such as \"simultaneous localization\", \"construction robots\", \"mapping\", and \"large-scale manipulator\". This cluster focuses on the spatial localization and mapping technologies used in construction robots. SLAM technology is crucial for robots, especially in construction settings, where robots need to adjust their position and actions based on real-time environmental information. Research in this area concentrates on how SLAM can enhance the autonomous navigation capabilities of construction robots, particularly in complex environments, and support large-scale construction tasks. Cluster 3 explores the broader field of technology, with keywords such as \"technology\", \"construction industry\", and \"robotics technology\". This cluster reflects the connections between construction robotics and various technological advancements. It includes the integration of robotics within the construction industry, examining the application of robots  
Figure 6: Keyword clustering network. Clusters (labeled 0–9) were identified using CiteSpace’s log-likelihood ratio (LLR) algorithm. Node colors represent clusters and labels indicate dominant themes. Data source: Web of Science Core Collection (2002–2024). in different construction activities. The main research direction is integrating emerging technologies like artificial intelligence, sensors, and data processing into construction robot systems, thereby enhancing the intelligence and efficiency of these robots. The prominence of \"human-robot collaboration\" (cluster 4) validates [PERSON]'s (2015) prediction of hybrid workflows but exposes a critical gap: current studies prioritize technical feasibility over socio-economic impacts.