Participatory design includes stakeholders in the development of products intended to solve real-life challenges. Involving end users in the design of robots is vital for developing effective, useful, acceptable and user-friendly products that meet expectations, needs, and preferences. This four-year international project developed and evaluated a home-based robot for mood stabilization and cognitive improvement in older adults with mild cognitive impairment and age-related health needs. The daily-care robot was developed in collaboration with experts, carers, relatives, and older adults, through six phases. Two phases were dedicated to cognitive stimulation games. This paper provides a summary of the participatory design and mixed-methods evaluation processes undertaken to develop, refine, and test the robot. The final robot and games were acceptable to older adults, and useful for delivering stimulating activities and providing reminders for medication, health and wellbeing checks. Personalization is required to optimize human-robot interaction, and imagery and speech should be consistent with local users. Functions should be personalizable to accommodate individual health needs and preferences. This project highlights the importance of participatory design and testing robotics in end-user environments, as technical issues associated with long-term use were uncovered. Recommendations for future development and the design of assistive health robots are made.

An aging global population and preference for aging-in-place pose the opportunity for home-based robots to assist older adults with their daily routines. However, there is limited research into the experiences of older adults using robots in their own homes. In this descriptive qualitative feasibility study, older self-supporting and community-dwelling adults with various age-related health needs used Bomy, a dailycare robot in their homes for up to one week. The study explored the usefulness of the robot and participants’ perceptions and experiences of using it. Bomy reminded them of daily activities and delivered cognitive stimulation games. Semi-structured in-person interviews were conducted, and data were analyzed thematically. Findings revealed an acceptance toward robots and the value of assistive dailycare robots. Participants perceived Bomy as a companion and made suggestions for improvement, including resolving technical issues associated with long-term use. Future functions should be personalizable, to accommodate each user’s health needs and could also include smoke detection and reading aloud functions. Dailycare robots show promising potential in elderly care, especially in providing reminders for medication, health and wellbeing. This study highlights the importance of co-design and testing robotics in the environments for which they have been developed. Widespread implementation of Bomy might be feasible in the future, with some further adjustments.

Robots have become increasingly present in our daily lives, and we see several settings wherein this technology might positively impact people. One of these settings, and the focus of this paper, is the museum. This paper provides an overview of the literature on how robots can help people within the museum context and explores the state-of-the-art methods or technologies employed by researchers to allow robots to interact within this environment. Five key features were found to be essential to integrate into social museum robots: social navigation (including safe and successful motions); perception (how robots can use visual skills to understand the environment); speech (verbal communication with visitors); gestures (non-verbal cues) and behavior generation (how the robot combines the four skills to adopt different behaviors). The paper subsequently analyzes the integration of these features into robotic systems for a complete and appropriate collection of behaviors in the museum setting.

Personalization and localization are important when developing social robots for different sectors, including education, industry, healthcare or restaurants. This allows for an adjustment of robot behaviors according to the needs, preferences or personality of an individual when referring to personalization or to the social conventions or the culture of a country when referring to localization. However, there are different models that enable personalization and localization presented in the current literature, each with their advantages and drawbacks. This work aims to help researchers in the field of social robotics by reviewing and analyzing different papers in this domain. We specifically focus our review by exploring different robots that employ distinct models for the adaptation of the robot to its environment. Additionally, we study an array of methods used to adapt the nonverbal and verbal skills of social robots, including state-of-the-art techniques in artificial intelligence.

Background: Sentiment expression and detection are crucial for effective and empathetic human-robot interaction. Previous work in this field often focuses on non-verbal emotion expression, such as facial expressions and gestures. Less is known about which specific prosodic speech elements are required in human-robot interaction. Our research question was: what prosodic elements are related to emotional speech in human-computer/robot interaction?Methods: The scoping review was conducted in alignment with the Arksey and O’Malley methods. Literature was identified from the SCOPUS, IEEE Xplore, ACM Digital Library and PsycINFO databases in May 2021. After screening and de-duplication, data were extracted into an Excel coding sheet and summarised.Results: Thirteen papers, published from 2012 to 2020 were included in the review. The most commonly used prosodic elements were tone/pitch (n = 8), loudness/volume (n = 6) speech speed (n = 4) and pauses (n = 3). Non-linguistic vocalisations (n = 1) were less frequently used. The prosodic elements were generally effective in helping to convey or detect emotion, but were less effective for negative sentiment (e.g., anger, fear, frustration, sadness and disgust).Discussion: Future research should explore the effectiveness of commonly used prosodic elements (tone, loudness, speed and pauses) in emotional speech, using larger sample sizes and real-life interaction scenarios. The success of prosody in conveying negative sentiment to humans may be improved with additional non-verbal cues (e.g., coloured light or motion). More research is needed to determine how these may be combined with prosody and which combination is most effective in human-robot affective interaction.

Background: For robots to be effectively used in health applications, they need to display appropriate social behaviors. A fundamental requirement in all social interactions is the ability to engage, maintain, and demonstrate attention. Attentional behaviors include leaning forward, self-disclosure, and changes in voice pitch. Objective: This study aimed to examine the effect of robot attentional behaviors on user perceptions and behaviors in a simulated health care interaction. Methods: A parallel randomized controlled trial with a 1:1:1:1 allocation ratio was conducted. We randomized participants to 1 of 4 experimental conditions before engaging in a scripted face-to-face interaction with a fully automated medical receptionist robot. Experimental conditions included a self-disclosure condition, voice pitch change condition, forward lean condition, and neutral condition. Participants completed paper-based postinteraction measures relating to engagement, perceived robot attention, and perceived robot empathy. We video recorded interactions and coded for participant attentional behaviors. Results: A total of 181 participants were recruited from the University of Auckland. Participants who interacted with the robot in the forward lean and self-disclosure conditions found the robot to be significantly more stimulating than those who interacted with the robot in the voice pitch or neutral conditions (P=.03). Participants in the forward lean, self-disclosure, and neutral conditions found the robot to be significantly more interesting than those in the voice pitch condition (P<.001). Participants in the forward lean and self-disclosure conditions spent significantly more time looking at the robot than participants in the neutral condition (P<.001). Significantly, more participants in the self-disclosure condition laughed during the interaction (P=.01), whereas significantly more participants in the forward lean condition leant toward the robot during the interaction (P<.001). Conclusions: The use of self-disclosure and forward lean by a health care robot can increase human engagement and attentional behaviors. Voice pitch changes did not increase attention or engagement. The small effects with regard to participant perceptions are potentially because of the limitations in self-report measures or a lack of comparison for most participants who had never interacted with a robot before. Further research could explore the use of self-disclosure and forward lean using a within-subjects design and in real health care settings.