Towards Equitable Robotic Furnishing Agents for Aging-in-Place: ADL-Grounded Design Exploration

TL;DR

This paper explores designing equitable robotic agents for aging-in-place, focusing on reducing daily living challenges for older adults through AI-powered, user-centered in-home robotic furnishing solutions.

Contribution

It introduces a novel ADL-grounded design approach for robotic agents that prioritize equity, safety, and user preferences in aging-in-place environments.

Findings

Older adults face challenges in organizing items, medication management, and transportation.

Participants prefer confirmation before robot actions and value predictability and transparency.

Design considerations include adjustable autonomy, multimodal feedback, and addressing equity concerns.

Abstract

In aging-in-place contexts, small difficulties in Activities of Daily Living (ADL) can accumulate, affecting well-being through fatigue, anxiety, reduced autonomy, and safety risks. This position paper argues that robotics for older adult wellbeing must move beyond "convenience features" and centre equity, justice, and responsibility. We conducted ADL-grounded semi-structured interviews with four adults in their 70s-80s, identifying recurrent challenges (finding/ organising items, taking medication, and transporting objects) and deriving requirements to reduce compounded cognitive-physical burden. Based on these insights, we propose an in-home robotic furnishing-agent concept leveraging computer vision and generative AI and LLMs for natural-language interaction, context-aware reminders, safe actuation, and user-centred transparency. We then report video-stimulated follow-up interviews with the same participants, highlighting preferences for confirmation before actuation, predictability, adjustable speed/autonomy, and multimodal feedback, as well as equity-related concerns. We conclude with open questions on evaluating and deploying equitable robotic wellbeing systems in real homes.