Towards Cognitive Robots That People Accept in Their Home

Abstract

It is intractable for assistive robots to have all functionalities pre-programmed prior to deployment. Rather, it is more realistic for robots to perform supplemental, on-site learning about user's needs and preferences, and particularities of the environment. This additional learning is especially helpful for care robots that assist with individualized caregiver activities in residential or assisted living facilities. As each care receiver has unique needs and those needs may change over time, robots require the ability to adapt and learn on-site. In this work, we propose the study design to investigate the impacts on end-users of observing robot learning. We will assess user attitudes towards robots that conduct some learning in the home as compared to a baseline condition where the robot is delivered fully capable. We will additionally compare different modes of learning to determine whether some are more likely to instill trust.