<p>Learning curves are critical to the safe adoption and standardized training of robot-assisted urological surgery, yet the evolution of proficiency assessment from technical experience toward surgical safety and functional recovery remains unclear. Records indexed in the Web of Science Core Collection were quantitatively mapped to examine publication dynamics, research partnerships, the underlying knowledge base, and shifts in major topics over time. A total of 346 publications, including 252 articles and 94 reviews, were analyzed. Scientific output increased markedly, with an annual growth rate of 21.33%. The United States was the leading contributor, while Vita-Salute San Raffaele University and Alexandre Mottrie were the most productive institution and author, respectively. Highly co-cited literature primarily focused on standardized complication assessment, procedure-specific learning curves, and perioperative outcomes. Keyword and temporal analyses revealed a gradual shift from initial experience and technical adaptation toward outcome-based evaluation of surgical proficiency. Perioperative outcomes, complications, and surgical experience dominated the research landscape, whereas functional recovery, quality of life, and other patient-centered outcomes remained comparatively underrepresented. Overall, learning curve research in robot-assisted urological surgery has progressed toward multidimensional assessment of clinical performance, but current frameworks remain strongly weighted toward perioperative safety. Future studies should establish procedure-specific, outcome-oriented models incorporating patient characteristics, procedural complexity, functional recovery, and multidisciplinary team performance to define more clinically meaningful standards of robotic surgical proficiency.</p>