Robots prove capable companion for older adults with mobility and memory challenges

Human-like interaction emerged as a non-negotiable feature. Older adults described ideal robot behavior in social terms: being friendly, polite, attentive, and intelligent. Many commented on the importance of using natural voice commands and receiving spoken feedback, likening ideal interactions with the robot to those with a reliable companion. Sensor capabilities were also essential; participants expected the robot to recognize medication, monitor user stress levels, detect obstacles, and respond appropriately to hand-offs during object transfers.

A new study published in Frontiers in Robotics and AI is reshaping the conversation around aging in place and the future of assistive robotics. The research, titled “Robotic Support for Older Adults with Cognitive and Mobility Impairments”, evaluates the functional capabilities of the Stretch RE2 robot in addressing the needs of older adults facing physical and cognitive challenges.

Led by researchers from the University of Illinois Urbana-Champaign, the study emphasizes how participatory design, real-world simulation, and gradual technological introduction can unlock the adoption of assistive robots in aging populations. The team surveyed 12 participants aged 60 to 97, with varied levels of cognitive and mobility impairments, to observe, interact with, and evaluate the Stretch robot in a realistic home environment.

The research was centered around three key questions: what capabilities a robot needs to support daily tasks, which tasks older adults prioritize for robotic assistance, and what factors influence or hinder adoption of assistive robots. The participants' feedback revealed that personalized autonomy, human-like communication, and real-time sensing are top priorities, alongside trust and ease of use as prerequisites for adoption.

What capabilities do older adults expect from assistive robots?

Participants expected the robot to not only carry out tasks but to do so autonomously, intuitively, and responsively. The Stretch robot's ability to deliver and retrieve items was well received, but users pushed further, requesting that the robot be able to initiate actions on its own based on environmental cues or user needs. Participants wanted it to identify hazards, execute scheduled routines, and correct its own errors. Robot autonomy, however, was not to replace human control, participants emphasized retaining the power to override or adjust the robot’s actions.

Human-like interaction emerged as a non-negotiable feature. Older adults described ideal robot behavior in social terms: being friendly, polite, attentive, and intelligent. Many commented on the importance of using natural voice commands and receiving spoken feedback, likening ideal interactions with the robot to those with a reliable companion. Sensor capabilities were also essential; participants expected the robot to recognize medication, monitor user stress levels, detect obstacles, and respond appropriately to hand-offs during object transfers.

Other technical demands included improved navigation, enhanced dexterity in robotic arms, and refined orientation controls. Users valued Stretch’s ability to move in tight spaces and adapt to different floor types but also called for smoother swiveling, faster mobility, and more sophisticated gripping. Communication remained central, users favored speech interfaces but also appreciated the inclusion of video call features via the robot’s tablet, which provided both social contact and practical reminders.

What tasks are most valuable for robotic assistance?

Across the board, participants prioritized two categories of support: physical and cognitive. High-demand physical tasks included delivering water, retrieving objects from the floor, helping open jars, and picking up trip hazards. These tasks reflected participants' difficulties with grip strength, balance, and mobility. Older adults with physical impairments identified specific household chores that became risk factors or sources of daily frustration, and which the robot could alleviate.

Cognitive tasks, such as reminders for medication, appointments, or wellness check-ins, were also ranked highly. Participants with memory challenges emphasized the relief that consistent, timely reminders would bring. Safety monitoring - an intersection of physical and cognitive support - emerged as another critical area. Participants envisioned the robot detecting a fall hazard, reminding them to turn off appliances, or even initiating emergency protocols in a crisis.

The study also highlighted a desire for socially enriching tasks. Several participants expressed interest in engaging the robot in storytelling, playing music, or facilitating social calls. While not critical for survival, these functions were seen as key to enhancing quality of life, reducing loneliness, and promoting mental well-being.

Participants’ responses to the System Usability Scale (SUS) placed Stretch above the industry average, indicating that the robot was easy to use and aligned with user expectations. Many noted that even a single robotic arm, when correctly programmed, could be useful for common household scenarios. However, some expressed interest in seeing future iterations of Stretch equipped with dual arms for greater versatility.

What factors influence robot adoption among older adults?

Trust, ease of use, and perceived usefulness emerged as the primary facilitators of robot adoption. After interacting with Stretch, 20% of participants reported increased trust in the robot’s reliability. The robot's ability to perform tasks consistently, coupled with intuitive control mechanisms, helped bridge the initial skepticism. No participant reported a decline in trust after the session, underscoring the effectiveness of the study’s gradual exposure methodology.

Usability ratings were bolstered by the robot’s simple interface, voice responsiveness, and low mental workload. The average workload score was moderate, with the highest demand being cognitive, primarily due to the initial novelty of the technology. The inclusion of familiar tools, like tablets for video calls, helped minimize perceived difficulty and enhance engagement.

Participants cited familiarity and relevance as essential factors in reducing technophobia. The study used a three-phase approach, introduction via video, observation of the robot in action, and direct interaction. This design successfully eased participants into the technology and allowed researchers to observe evolving attitudes in real time. The realistic home simulation also played a key role in helping participants imagine daily life with the robot and identify gaps between what it could do and what they needed.

Despite the overwhelmingly positive response, barriers remained. Some users expressed concerns about the robot’s ability to perform dual-arm tasks, the limitations of a fixed interaction model, and the long-term durability of such devices in a home setting. Others suggested that the robot should avoid performing tasks users could still do themselves to prevent dependency. Future iterations of assistive robots must therefore balance autonomy with human agency, offering support without undermining independence.

Moreover, the study identified indirect adoption drivers. Participants appreciated the idea that Stretch could act as a social liaison, connecting them to caregivers or distant family members via video call, particularly when mobility or cognitive challenges made such interactions difficult. This dual utility, combining functional assistance with emotional connection, was especially meaningful for those facing isolation.