A Social Robot Reading Partner for Explorative Guidance

Zhang, Xiajie; Breazeal, Cynthia; Park, Hae Won

doi:10.1145/3568162.3576968

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…We created an 11-element vector, called 𝑠 𝑡 , to represent the observation state for the coaching dialogue flow, which consists of: prediction of interaction rupture (present or absent), current well-being exercise (savouring, gratitude, accomplishment, one door closes one door opens), speech features (duration of speech and silence), and previous actions (summarisation, follow-up question, and new episode). All of these features were collected at the end of each turn 𝑡 to keep track of the dialogue flow and the conversational interchange between the human coachee and the robotic coach, as in [52]. The actions 𝑎 𝑡 were 3 discrete dialogue actions of the robotic coach that can decide the coaching dialogue flow of the well-being practice, namely (1) summarise what the coachee said, (2) ask for a follow-up question (e.g., "How does this event make you feel?…”

Section: Reinforcement Learning Problem Formulationmentioning

confidence: 99%

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Robotic Mental Well-being Coaches for the Workplace

Spitale

Axelsson

Güneş

2023

Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction

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Recently, several works have explored if and how robotic coaches can promote and maintain mental well-being in different settings. However, findings from these studies revealed that these robotic coaches are not ready to be used and deployed in real-world settings due to several limitations that span from technological challenges to coaching success. To overcome these challenges, this paper presents VITA, a novel multi-modal LLM-based system that allows robotic coaches to autonomously adapt to the coachee's multi-modal behaviours (facial valence and speech duration) and deliver coaching exercises in order to promote mental well-being in adults. We identified five objectives that correspond to the challenges in the recent literature, and we show how the VITA system addresses these via experimental validations that include one in-lab pilot study (𝑁 = 4) that enabled us to test different robotic coach configurations (pre-scripted, generic, and adaptive models) and inform its design for using it in the real world, and one real-world study (𝑁 = 17) conducted in a workplace over 4 weeks. Our results show that: (i) coachees perceived the VITA adaptive and generic configurations more positively than the pre-scripted one, and they felt understood and heard by the adaptive robotic coach, (ii) the VITA adaptive robotic coach kept learning successfully by personalising to each coachee over time and did not detect any interaction ruptures during the coaching, (iii) coachees had significant mental well-being improvements via the VITA-based robotic coach practice. The code for the VITA system is openly available via https://github.com/Cambridge-AFAR/VITA-system. CCS Concepts: • Human-centered computing → Empirical studies in HCI ; HCI theory, concepts and models.

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Section: Reinforcement Learning Problem Formulationmentioning

confidence: 99%

“…The results showed that there were not significant differences among the three models. We then chose the DQN as it is the most commonly used one in discrete problems, e.g., [52].…”

Section: Reinforcement Learning Problem Formulationmentioning

confidence: 99%

Robotic Mental Well-being Coaches for the Workplace

Spitale

Axelsson

Güneş

2023

Proceedings of the 2023 ACM/IEEE International Conference on Human-Robot Interaction

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Human–Robot Companionship: Current Trends and Future Agenda

Ahmed,

Buruk,

Hamari

2024

Int J of Soc Robotics

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The field of robotics has grown exponentially over the years, especially the social aspect, which has enabled robots to interact with humans meaningfully. Robots are now used in many domains, such as manufacturing, healthcare, education, entertainment, rehabilitation, etc. Along with their widespread usage in many real-life environments, robots have been used as companions to humans. With the increased amount of research done on human–robot companionship (HRC), it is important to understand how this domain is developing, in which direction, and what the future might hold. There is also a need to understand the influencing factors and what kind of empirical results are in the literature. To address these questions, we conducted a systematic literature review and analyzed a final number of 134 relevant articles. The findings suggest that anthropomorphic and zoomorphic robots are more popular as human companions, while there is a lack of interest in functional and caricatured robots. Also, human-like and animal-like features are implemented more in companion robots. Studies rarely exploit the mobility available in these robots in companionship scenarios, especially in outdoor settings. In addition to that, co-existence and co-performance-based implementation with humans have been observed rarely. Based on the results, we propose a future research agenda that includes thematic, theoretical, methodological, and technological agendas. This study will help us understand the current state and usage of robotic companions which will then potentially aid in determining how HRC can be leveraged and integrated more seamlessly into human lives for better effectiveness.

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