Applying Kansei/Affective Engineering Methodologies in the Design of Social and Service Robots: A Systematic Review

Abstract

This article provides a systematic review of research articles applying Kansei / Affective Engineering methodologies for the development of Social and Service Robots. We describe relevant concepts and main types of Kansei Engineering methodologies to assist new researchers and practitioners interested in the area. We also summarize the main objectives and findings of eleven peer-reviewed research articles published in relevant conferences and journals. We selected these articles after performing a systematic search in relevant databases for robotics research (Science Direct, Web of Science, IEEE Xplore, ACM digital library, and Springer Link) and Kansei Engineering (J-STAGE). This search includes studies published in the English language between 1999 and 2019. Findings from observed articles indicate that Kansei Engineering is a suitable paradigm for robot design. Moreover, developers can use Kansei Engineering methodologies to identify and better understand the design aspects enabling social and service robots to be accepted and desired by users. Contributions of articles reviewed include (i) the use of novel approaches for grasping emotional reactions in Human–Robot Interaction experiments and (ii) the proposal of guidelines for designing social and service robots. However, the use of Kansei Engineering methodologies in robotics is still a poorly explored area. Therefore, we describe possible future directions and open challenges.