Human-robot interaction: predicting research agenda by long short-term memory.

ABSTRACT: The article addresses the identification and prediction of research topics in human-robot interaction (HRI), fundamental in Industry 4.0 (I4.0) and future Industry 5.0 (I5.0). In the absence of research agendas in the scientific literature, the study proposes a multilayered model to create a precise agenda to guide the scientific community in new developments in collaborative robotics and HRI technologies. The methodology is divided into four stages, which make up the three layers of the model. In the first two stages, scientific articles on HRI for the period 2020-2021 were collected and analyzed using data mining techniques together with VantagePoint and Gephi software to identify keywords and their relationships. These initial stages form layer 1 of the model, where the main scientific

SUBMITTER: Borregan-Alvarado J 

PROVIDER: S-EPMC11623198 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature