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Physical exercise has many physical, psychological and social health benefits leading to improved life quality. This paper presents a robotic system developed as a personal coach for older adults aiming to motivate older adults to participate in physical activities. The robot instructs the participants, demonstrates the exercises and provides real-time corrective and positive feedback according to the participant’s performance as monitored by an RGB-D camera. Two robotic systems based on two different humanoid robots (Nao, toy-like and Poppy, mechanical-like) were developed and implemented using the Python programming language. Experimental studies with 32 older adults were conducted, to determine the preferable mode and timing of the feedback provided to the user to accommodate user preferences, motivate the users and improve their interaction with the system. Additionally, user preferences with regards to the two different humanoid robots used were explored. The results revealed that the system motivated the older adults to engage more in physical exercises. The type and timing of feedback influenced this engagement. Most of these older adults also perceived the system as very useful, easy to use, had a positive attitude towards the system and noted their intention to use it. Most users preferred the more mechanical looking robot (Poppy) over the toy-like robot (Nao).

AbstractFeedback design is an important aspect in person-following robots for older adults. This paper presents a user-centered design approach to ensure the design is focused on users’ needs and preferences. A sequence of user studies with a total of 35 older adults (aged 62 years and older) was conducted to explore their preferences regarding feedback parameters for a socially assistive person-following robot. The preferred level of robot transparency and the desired content for the feedback was first explored. This was followed by an assessment of the preferred mode and timing of feedback. The chosen feedback parameters were then implemented and evaluated in a final experiment to evaluate the effectiveness of the design. Results revealed that older adults preferred to receive only basic status information. They preferred voice feedback over tone, and at a continuous rate to keep them constantly aware of the state and actions of the robot. The outcome of the study is a further step towards feedback design guidelines that could improve interaction quality in person-following robots for older adults.

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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