NeuroDesign in Human–Robot Interaction, Volume 2: Translational Brain–Body–Robot Loops for Adaptive, Trustworthy, and Embodied HRI

This Research Topic is the second volume in the series, the first volume can be found here; NeuroDesign in Human-Robot Interaction: The making of engaging HRI technology your brain can’t resistHumans are embodied, adaptive, emotional, and socially situated beings, with complex brain information processing, cognitive perception, reasoning, affective responses, and sensorimotor capabilities. Technologies designed to interact with humans must address not only functional performance, but also the neural, cognitive, affective, ergonomic, neuromuscular, and social dimensions of interaction. This holistic approach is especially important in Human–Robot Interaction (HRI), where robots closely collaborate with people across homes, hospitals, rehabilitation clinics, workplaces, public spaces, educational settings, and immersive environments.Although recent advances in robotics and AI, wearable sensing, neurotechnology, and interactive systems have significantly expanded the technical capabilities of robots, many robots still struggle to understand personalized human intentions, attention, workload, emotions, trust, fatigue, movement constraints, and context-dependent requirements. As a result, human-robot interactions often remain effortful, unpredictable, insufficiently personalized, or poorly aligned with human expectations and abilities.NeuroDesign in HRI differs from general neurorobotics by moving beyond biologically inspired robot control to emphasize human-facing interaction design grounded in the human brain, body, behavior, and experience. The first volume of this Research Topic introduced NeuroDesign in HRI as an interdisciplinary framework for designing robots with the human brain and body in mind. It brought together neuroscience, cognitive and behavioral psychology, robotics, artificial intelligence, neuroengineering, wearable technologies, biomechanics, and interaction design to support human–robot systems that are cognitively aligned, physiologically responsive, emotionally appropriate, and ergonomically compatible.Building on this foundation, Volume 2 shifts the focus from conceptual exploration to translational implementation. It examines how NeuroDesign principles can be transformed into measurable design methods, closed-loop systems, evaluation protocols, datasets, adaptive algorithms, and real-world HRI applications. The goal is not simply to use neuroscience or AI as inspiration, but to operationalize brain–body–robot interaction as a practical framework for designing, controlling, evaluating, and deploying next-generation cognitive HRI (cHRI) and physical HRI (pHRI) systems, as well as their convergence in socially situated and embodied human–robot interaction.Furthermore, recent advances in foundation models, large language models, vision-language-action models, generative AI, embodied AI, and neuro-symbolic AI create new opportunities for NeuroDesign in HRI. These technologies may enable robots to interpret multimodal human signals, communicate more naturally, adapt across users and contexts, generate context-aware actions, and support explainable interaction. However, their use in NeuroDesign must be grounded in human-centered evidence, ethical awareness, and measurable interaction outcomes. Contributions involving AI models are especially encouraged when they demonstrate how such models improve human-state understanding, closed-loop adaptation, transparency, personalization, embodied coordination, or real-world usability in HRI.This Research Topic welcomes translational, theoretical, methodological, experimental, design-oriented, and application-driven contributions that advance NeuroDesign as a concrete approach to brain- and body-centered HRI. We particularly encourage studies that include measurable human-centered outcomes, such as cognitive workload, trust calibration, intention recognition, emotional response, physiological adaptation, motor coordination, ergonomic comfort, safety, agency, engagement, learning, rehabilitation progress, long-term acceptance, or real-world deployment performance.This Research Topic invites contributions on topics including, but not limited to:• NeuroDesign theories, principles, frameworks, and methodologies for brain- and body-centered human–robot interaction (HRI)• Cognitive HRI (cHRI), physical HRI (pHRI), and social HRI (sHRI) informed by neuroscience, psychology, biomechanics, and human-centered design• Brain–computer and brain–machine interfaces (BCI/BMI), neuroadaptive systems, and human-in-the-loop co-learning approaches for robotic control• Multimodal sensing, reasoning, interaction, and physiological computing using EEG, fNIRS, EMG, EOG, ECG/HRV, skin conductance, eye tracking, speech, gesture, motion, force, tactile signals, and behavioral data• Computational modeling and decoding of human intent, attention, workload, emotion, trust, agency, engagement, and social signals for adaptive HRI• Foundation models, large language models (LLMs), vision-language-action models (VLAs), generative AI, embodied AI, and neuro-symbolic AI for natural, explainable, trustworthy, and context-aware HRI• Wearable robotics, haptic interfaces, and neuroergonomic technologies for enhancing and augmenting human perception, movement, comfort, safety, and performance in HRIThis Research Topic is linked with the NeuroDesign in HRI workshop, which took place at 2026 IEEE International Conference on Robotics and Automation (ICRA 2026). Any contributions presented at the workshop must be extended to contain 30% original content. However, this Research Topic welcomes relevant contributions that were not presented at the workshop. Topic editors: Ker-Jiun Wang, Tharun Kumar Reddy, Zhi-Hong Mao, Ramana Vinjamuri, Maryam Alimardani, Silvia Tolu Source: https://www.frontiersin.org/research-topics/76786/neurodesign-in-human-robot-interaction-volume-2-translational-brain-body-robot-loops-for-adaptive-trustworthy-and-embodied-hri