Understanding future opportunities in robotics technology: a comprehensive analysis of research and innovation trends

Oğuz Özbay (), Serhat Burmaoğlu () and Erol Taymaz ()
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Oğuz Özbay: TÜBİTAK National Metrology Institute (UME)
Serhat Burmaoğlu: İzmir Kâtip Çelebi University, Department of Data Science and Analytics, Faculty of Economics and Administrative Sciences
Erol Taymaz: Middle East Technical University, Department of Economics

Scientometrics, 2025, vol. 130, issue 11, No 14, 6253-6287

Abstract: Abstract This study investigates the future opportunities and development trajectories of robotics technology through comprehensive analysis of research trends and technological developments. By examining over 268.000 scientific publications and 343.000 patents in the robotics domain, the research provides insights into emerging technological patterns and their potential societal implications. Moreover, this study provides a methodological framework for future-oriented technology analysis (FTA) that extends beyond robotics to other technological domains. The analysis, supported by advanced text mining techniques including Topic Modeling and semantic analysis, identified 91 distinct research topics and 98 patent topics, revealing significant trends in robotics development across various sectors including manufacturing, healthcare, service robotics, and human–robot interaction. The findings highlight the increasing convergence of artificial intelligence with robotics, the growing importance of collaborative robots, and the emergence of novel applications in healthcare and social assistance. The study demonstrates how robotics technology is evolving beyond traditional industrial applications into more sophisticated and socially integrated systems. By analyzing these patterns within the framework of FTA, this research offers valuable data-driven insights for policymakers, industries, and researchers in understanding and preparing for future developments in robotics technology. The findings contribute to both theoretical understanding of robotics evolution and practical applications, providing strategic insights for stakeholders navigating the future landscape of robotics technology.

Keywords: Robotics technology foresight; Future technology analysis via text mining; Technological evolution; Innovation patterns; Word mover’s distance; Word embedding; Structural topic model (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11192-025-05464-2

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