Keyword-based technology radar based on IEEE conference papers on human-robot interaction

Abstract

Knowledge on emerging technologies is essential for a forward-looking development regarding human-centered design and implementation. There are different possibilities of mapping the state of the art and forecasting future developments, for example employer and employees surveys of technology diffusion, expert Delphi surveys, mapping news media or analyzing sales data. In this paper, we test an approach based on the analysis of keywords from IEEE conference papers in the field of human-robot interaction. For this reason, we analyzed all given keywords of IEEE conference papers from 2015 until 2019 in the field of human-robot interaction. We calculated and visualized the frequencies of given keywords per year, identified the most frequent keyword pairs as well as correlations among the most frequent keywords using the software package R. The results show an emerging trend towards artificial intelligence, consistencies in mobile robotics and for example a decline in telerobotics. Additionally, we found strong interconnections of keyword pairs, highlighting subdomains in the research field. Correlation analysis helped further understanding the relationship within keyword clusters. Limitations of this approach are that any kind of knowledge structure is inherently incomplete. We avoided standardization issues presented in prior keyword publications by using controlled keywords.