This paper explores the elements that are needed to facilitate the seamless transfer of a robotic agent’s "persona" between various embodiments. It addresses the challenges in maintaining the robot identity, user trust, and engagement during transitions into other robot embodiments. Through a literature review, we propose a framework for decomposing and reconstructing a robot’s persona across embodiments, integrating visual, audial, and behavioral identity signals. By leveraging insights from robot interaction studies, this research contributes to the design of transferable and adaptable robot companions, with applications in eldercare and assistive technologies. The findings have broader implications for advancing human-robot interaction and fostering sustainable, user-centered robotic systems.

The interaction between humans and robots transcends mere utility, venturing into the realm of emotional bonds and perceived lifespans. Through a review of the literature and poignant case studies, this article reveals the intricate language and sentiments expressed by individuals as they navigate the loss of their mechanical companions. This exploration is relevant to understanding the complex social and emotional relationships that can form between humans and robots, emphasizing the need for thoughtful consideration of the life-cycle management of social robots. This research also underscores a significant gap in existing literature and industrial practices: the end-of-life phase of robots and the consequential emotional toll on humans.

Robot designers and Human-Robot Interaction (HRI) practitioners can face challenges when people form a mental model of a robot that is not appropriate. Although the field of robotics would benefit significantly from a broad representation of designers, there is currently no comprehensive method of including many people in the design process and no theory of what expectations a robot design feature might elicit. We seek to address these challenges through the creation of a robot design platform, an online tool similar to a character creation interface in a video game, where users create a robot design. By collecting a large number of robot designs from users, we seek to be able to identify aspects of a robot’s design that influence the mental models humans ascribe to the robot. To maximize the universal usability of the platform, we conducted a three-part survey to assess which icons should be used to visually represent the mental states ascribed to the robots created by users on the platform. In our assessment, we found nine icons that met our criteria for use in the platform and others that should be further evaluated.

This work presents our strategy for investigating the fundamental guidelines and theories related to robot mind perception, and for establishing a metric for mental models, using our web-based tool, Build-A-Bot. We also discuss the effectiveness and efficiency of our platform by virtue of its inclusive design and its ability to visualize the user’s intended representation of a mental model for a robot through a 3D game-like interface. We conducted an observational user test study to assess if the website and the embedded robot building tool are effective and efficient to use for users. We found that the design of the robot creation platform and its associated website are considered intuitive and effective by a majority of our survey population. The Build-A-Bot platform successfully provides the ability for users to visualize their ideal representation of their mental model through an interactive game. Based on the obtained data, we propose further steps to optimize the Build-A-Bot platform for universal usability