This study provides user-studies aimed at exploring factors influencing the interaction between older adults and a robotic table setting assistant. The influence of level of automation (LOA) and level of transparency (LOT) on the quality of the interaction was considered. Results revealed that the interaction effect of LOA and LOT significantly influenced the interaction. A lower LOA which required the user to control some of the actions of the robot influenced the older adults to participate more in the interaction when the LOT was low compared to situations with higher LOT (more information) and higher LOA (more robot autonomy). Even though, the higher LOA influenced more fluency in the interaction, the lower LOA encouraged a more collaborative form of interaction which is a priority in the design of robotic aids for older adult users. The results provide some insights into shared control designs which accommodates the preferences of the older adult users as they interact with robotic aids such as the table setting robot used in this study

It is important to encourage older adults to remain active when interacting with assistive robots. This study proposes a schematic model for integrating levels of automation (LOAs) and transparency (LoTs) in assistive robots to match the preferences and expectations of older adults. Metrics to evaluate LOA and LoT design combinations are defined. We develop two distinctive test cases to examine interaction design considerations for robots working for this population in everyday tasks: a person-following task with a mobile robot and a table-setting task with a robot manipulator. Evaluations in user studies with older adults reveal that LOA and LoT combinations influence interaction elements. Low LOA and high LoT encouraged activity engagement while receiving adequate information regarding the robot's behavior. The variety of objective and subjective metrics is essential to provide a holistic framework for evaluating the interaction. Index Terms-Assistive robots (ARs), human-robot interaction, interaction design, level of automation (LOA), level of transparency (LoT), older adults, socially ARs. I. BACKGROUNDT HE GLOBAL population of older adults (aged 65+) is increasing rapidly without commensurate growth in people that can support them [1]. This shortage is creating an eldercare gap in which the scarcity of caregivers, social support, and healthcare professionals has left many in this group facing many barriers in aging [2]. Assistive robots (ARs) can help reduce these barriers, facilitate independence, and promote more successful aging (e.g., [3]-[5]). While there has been progress in AR design and development for many daily applications [6],

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