Exploration of Service Robot Morphology Through Generative AI Applications

Abstract

Advancements in robotics and artificial intelligence (AI) are bringing service robots into various aspects of our lives, and the appearance of service robots has diversified along with their increase. While anthropomorphic design has been extensively discussed in human-robot interaction (HRI) as a way of making robots more understandable and acceptable, much remains to be investigated about the desired level of human-likeness in a robot’s design, which is also dependent on the specific context of use. This paper proposes a visual mapping method as a means of guiding the appearance and degree of human-likeness of a service robot in the corresponding use context. A service robot context map, comprising the robot’s task nature and operation environment, is constructed and translated into a morphology map regarding the level of human-likeness and aesthetic qualities. Based on these mappings, two service robot contexts were selected to create evaluation materials to measure the desired degree of human-likeness. Variations of a service robot design were created and visualized in photorealistic rendering through the utilization of generative image AI tools. Though with some unintended design changes, generative image AI is an efficient way of creating robot representations in context for an evaluation study.

Keywords: Industrial Design, Human-Robot Interaction, Robot Morphology, Service Robot, Generative Image Ai

DOI: 10.54941/ahfe1005117