Abstract: Assistive in-home robots have the potential to enable older adults to age in place by offloading mentally or physically demanding tasks to a robot. However, one challenge for in-home robots is that each individual will have differing needs, preferences, and home environments, which can all change over time. Learning from Demonstration (LfD) is one solution to enable non-expert users to communicate their differing and changing preferences to a robot, but LfD has not been evaluated with a population of older adults. In a human-subjects experiment where participants teach a robot via LfD, we characterize disparities between older and younger adult participants in terms of robot performance, usability, and participant perceptions. We find that older adults are significantly more critical of the robot’s performance and found the LfD process less usable than younger adults. Based on participant performance and feedback, we present design guidelines that will enable roboticists to increase LfD accessibility across demographics.
