The field of Human-Robot Interaction (HRI) is characterized by its dynamic evolution, showcasing the potential for robots to assimilate into human life across diverse settings like social domains, healthcare, education, and industry. Traditional HRI research often revolved around static models and narrowly focused dynamics, with robots programmed under limited and predefined contexts. However, recent studies underline a substantial need for frameworks that are adaptive, context-sensitive, and capable of evolving beyond these foundational models. Yet, there remains an array of unaddressed challenges, which, if tackled, could revolutionize the robustness and applicability of robot integrations in daily human interactions.

This Research Topic aims to bridge the existing gaps within the HRI field by scrutinizing and pushing past the traditional frameworks used to analyze human-robot interactions. The goal is to unveil new facets of robot personality, enhance the adaptability of robotic behaviors in real-time scenarios, and delve deeper into the multimodal interactions within human-robot relationships over extended periods. Beyond expanding theoretical boundaries, this Research Topic seeks to test and validate new models that could predict and improve the dynamics of future human-robot interactions, drastically impacting the design and functionality of robots in various sectors.

We explicitly welcome contributions that explore different types of models/frameworks relevant to HRI, including:

● ecosystems and data infrastructures for configuring and managing robots across diverse contexts of use,
● frameworks or models for analyzing HRI from psychological, sociological, or interactional perspectives,
● and theoretical models of interaction dynamics between humans and robots over time.

Within these areas, we welcome articles addressing, but not limited to, the following themes:

● Ecosystems for configuring and managing robots in healthy aging.
● Frameworks for studying and analyzing multi actor human-robot interaction
● Models for analyzing the impact of differing contexts on human-robot interaction dynamics.
● Implementations and impacts of non-traditional personality models in robot design.
● Context-moderation models (social, trust, task, personalization) estimating how settings or user factors modulate outcomes from adapted robot behaviors.
● Methodological frameworks and theoretical expansions in human-robot companionship studies.

This Research Topic encourages interdisciplinary submissions analyzing ethical, psychological, and societal impacts pivotal to the development and deployment of robots, especially in sensitive areas like healthcare and therapy. Researchers from various disciplines such as robotics, AI, HCI, psychology, and the social sciences, along with industry professionals, are encouraged to contribute, fostering a multidisciplinary dialogue to enhance the efficacy and acceptability of human-robot interactions.

Are you interested in contributing a manuscript to this Research Topic?

Advancements in Human-Robot Interaction: Beyond Traditional Frameworks and Models