The overall goal of the novel Functionality, Usability, Look-and-Feel, and Evaluation (FULE) user-centered methodology for product design proposed in this paper is to develop usable and aesthetic products. Comprising several product design methods, this novel methodology we devised focuses on the product designer’s role and responsibility. Following the first three formative assessment phases that define the product’s functionality, usability, and look-and-feel, the summative evaluation phase not only assesses the product, but also provide guidelines to its implementation, marketing, and support. A case study devoted to the design of an autonomous medical device illustrates how the FULE methodology can provide the designer with tools to better select among design alternatives and contribute to reducing bias and subjective decisions.

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Robots' visual qualities (VQs) impact people's perception of their characteristics and affect users' behaviors and attitudes toward the robot. Recent years point toward a growing need for Socially Assistive Robots (SARs) in various contexts and functions, interacting with various users. Since SAR types have functional differences, the user experience must vary by the context of use, functionality, user characteristics, and environmental conditions. Still, SAR manufacturers often design and deploy the same robotic embodiment for diverse contexts. We argue that the visual design of SARs requires a more scientific approach considering their multiple evolving roles in future society. In this work, we define four contextual layers: the domain in which the SAR exists, the physical environment, its intended users, and the robot's role. Via an online questionnaire, we collected potential users' expectations regarding the desired characteristics and visual qualities of four different SARs: a service robot for an assisted living/retirement residence facility, a medical assistant robot for a hospital environment, a COVID-19 officer robot, and a personal assistant robot for domestic use. Results indicated that users' expectations differ regarding the robot's desired characteristics and the anticipated visual qualities for each context and use case.

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