In assistive robotics – a sub-discipline within the broader field of human-robot interaction (HRI) concerned with designing autonomous agents that can support people with disabilities (PWDs) – HRI designers use User-Centered Design (UCD) approaches to create assistive robots and technologies. They involve potential end-users with disabilities as a way of ensuring the end-product, that is, the assistive robot, is usable; in this process, the focus remains on creating an assistive robot that is predicated on the professional designer’s (i.e., the roboticists) understanding of the problem space and evaluating the system’s performance. While Participatory Design (PD) paradigms – democratic approaches aimed at shifting power relations and integrating community interests in design processes outcomes  – are becoming commonplace in HRI, designers seldom interrogate how or whether these systems fit into the daily lives and address the needs of PwDs; furthermore, PD or cooperative design (“co-design”) engagements facilitated by HRI researchers often include HRI professionals whose technical expertise is highly regarded, while the involvement of PwDs is relegated to that as the “expert user” used to sanity check design ideations. Still, designing with non-professional designers, including PwDs, can be challenging. People who are unfamiliar with the process of design, such as design thinking, which is the practice of generating and implementing design ideations, are often not versed with the jargon and methods that comprise professional design practice, which can be intimidating and exclusionary.

In this thesis, I present the lived experience as a framework for co-designing physically and socially supportive agents (i.e., the behaviors, functions, and features) with people with disabilities (PwDs) who are non-professional designers. Throughout this thesis, I demonstrate robotic technologies that are functionally “assistive” – that is, they assist in complex daily tasks, such as robotic navigation devices; I also present robotic technologies that are “supportive” (which comprises “assistive” agents); that is, they connect people to resources, such as delivery robots, and activities, such as social agents to encourage or maintain emotional wellbeing. Through this work, I reveal that situating design ideation in non-professional designers’ lived experiences (i.e., the tasks they perform daily, the challenges that emerge, and the ways that they envision assistive and supportive robotic technologies intervening in and remediating these challenges) yields rich and specific design recommendations. Additionally, our findings suggest that participatory encounters with PwDs that are grounded in the lived experience can be made more approachable and sustain participation in iterative design engagements (as evidenced through turnout in multi-session encounters).

In this thesis, I provide theoretical grounding for the “lived experience” across philosophical and critical study, technology design practice, and robotics and present three works (1 completed, 2 in-progress) that demonstrate the effectiveness of engaging with the lived experience of non-professional designers with disability. These works include: 1) co-designing robotic mobility devices with who are blind or have low vision; 2) pluriversal (i.e., the richness and diversity of lived experience that comprises a single person’s life) design engagements with people with mobility and visual disabilities on improving the accessibility of on-demand, last-mile delivery delivery robots; and finally, 3) first-person and co-design engagements towards designing socially assistive agents that support emotional wellbeing by facilitating joint artmaking and co-regulation strategies. Through this work, I provide design recommendations for developers creating robotics technologies that are aimed at supporting PwDs. Furthermore, I demonstrate that PD practices that hinge on the lived experience bolster engagement and yield rich insights that can inform specific design recommendations for assistive robots.