User Experience and Interaction Design for Non-Anthropomorphic Robots in Work Contexts

Abstract

This thesis examines the user experience of non-anthropomorphic robots in contemporary workplace settings. These robots are increasingly deployed in work environments such as hospitals, factories, and logistics facilities, yet their limited expressive capabilities often lead to challenges in communication, transparency, and role interpretation. While non-anthropomorphic robots express functional intent and avoid issues associated with human-like designs, they can also hinder effective interaction, particularly among users who lack familiarity with robots. Research on the user experience of such robots in real work contexts remains limited, creating a gap in understanding how workers perceive, interpret, and collaborate with these systems.

The goal of this thesis is two-fold. First, it explores the current user experiences of non-anthropomorphic robots in the workplace and identifies UX factors that inform the design of interactions with such robots. Second, this thesis develops a design model and a practical design tool for robot interaction designers. The thesis addresses three research questions: 1. What are the user experiences of non-anthropomorphic robots in the context of work? 2. What factors influence the user experience of non-anthropomorphic robots in workplace environments? 3. How can these UX factors inform the design of non-anthropomorphic robot interactions? The work integrates four empirical studies conducted in workplace contexts: three qualitative and one mixed-method. Methods include user interviews, contextual inquiries, codesign workshops, and an online survey. Study 1 identifies core user-experience themes when user collaborate with a robot arm, including safety, trust, accomplishment, confusion, and emergent fellowship. Study 2 shows that a clear robot role, context-appropriate personality, and playful interactions can improve acceptance and interaction fluency. Study 3 demonstrates that personality-relevant behavior may positively affect acceptance of a non-anthropomorphic wellness robot even when the intended personality is not explicitly recognized by users. Study 4 identifies ten context-dependent robot communication themes and shows that the same light, motion, or sound cues are interpreted differently by users across scenarios, emphasizing the need for adaptive, context-sensitive signaling.

The scientific contribution of this thesis is conceptual and methodological. The thesis findings offer a human-centered perspective that advances understanding of how user experience can be shaped in interactions with automated and autonomous machines. This contribution is relevant not only for designers of non-anthropomorphic robot interactions but also for industrial and service designers working with robotic systems in industrial, factory, and logistics contexts. In addition, the practical contribution of the thesis advances human-robot interaction design by introducing a structured design approach. As an outcome of this research, a design model called the SOCKS model (Specify UX goals, Outline communication goals, Calibrate behavior, Knit the personality, and Signal via interaction modalities) is presented. Based on the SOCKS model, a practical design tool was developed to support robot interaction designers in applying the research findings in their work. This tool is presented in the form of a design canvas, the NARID (Non-Anthropomorphic Robot Interaction Design) canvas, which facilitates and structures the interaction design process. While not all elements of the model and canvas are exclusive to workplace contexts, several components, such as the specification of UX goals and the definition of the robot’s personality have been developed with a particular focus on work environments.