Touch is a fundamental communication modality in human-robot interaction and may support grounding, emotional regulation, and stress reduction in therapeutic contexts. However, designing touch-based interactions for individuals with post-traumatic stress disorder (PTSD) requires careful consideration of trauma-informed care (TIC) principles, including safety, transparency, autonomy, and trigger avoidance. This paper investigates how touch actuation in social robots can be designed to align with trauma-informed care. We distinguish between direct touch, involving physical contact between a user and a robot, and indirect touch, mediated through artifacts such as wearables or smart textiles. Building on this distinction, we propose a design space comprising three dimensions: Actuation Modality, Objective of the Actuation, and Intended Effect of the Actuation. We analyze these dimensions through the lens of trauma-informed care and derive key design considerations for touch-based interventions. The resulting approach provides a conceptual foundation for developing trauma-sensitive social robots that support individuals with PTSD through touch-based interactions.
Virtual Reality (VR) offers a flexible and controllable platform for studying human-robot interaction. Prior work has explored VR for socially aware robot navigation. However, whether VR captures the multimodal interaction dynamics observed in real-world human-robot co-navigation…
Tactile sensing can substantially improve contact-rich robotic manipulation, yet its practical deployment remains limited by the fragility, calibration requirements, and maintenance burden of tactile hardware. This raises a fundamental question: can robots benefit from tactile kn…
Effective social robot navigation requires sensitivity to human behavior, often revealed through subtle skeletal cues like gait and orientation. We present Human-Aware Implicit Social Robot Navigation (HumAIN), a novel framework that fuses implicit social cues directly into the p…
Tactile sensing for social-physical human-robot interaction (spHRI) is designed in a hardware-driven manner, where predefined sensor configurations constrain coverage, spatial resolution, and the range of recognizable gestures. We propose a requirement-driven framework that deriv…
When designing robots' nonverbal behaviors, many researchers have turned to arts-based insights, such as Disney's Animation Principles. Yet, while these principles bear key insights into the design of like-life characters, their application to robot design is inherently limited,…
Vision Language Models (VLMs) enable robots to visually perceive their environment as well as the actions and characteristics of their conversation partner or humans in collaboration. Especially for social robots deployed in everyday settings and for uncomplicated, natural use, i…