With growing research on haptic interfaces, Mediated Social Touch (MST) technologies offer the potential to record, synthesise, and reproduce (RSR) touch experiences across space and time, enabling, for instance, a hug from afar and from the past. Although much of the existing research highlights the direct benefits of these systems, such as reducing loneliness and providing emotional support, little attention has been paid to their broader sociotechnical impacts. To address this gap, we used the Future Ripples method to speculate on possible effects of MST. We conducted three workshops with 24 participants, including potential users, domain experts, and haptics researchers. Throughout these sessions, participants collectively envisioned possible future scenarios, alongside opportunities and threats, and proposed actionable responses. Our qualitative analysis organised these insights into four themes and three distinctive challenges. These findings offer haptics researchers intervention points across the RSR pipeline to inform MST design, alongside methodological insights from applying Future Ripples to MST technology.

While visual augmentation dominates the augmented reality landscape, devices like Meta Ray-Ban audio smart glasses signal growing industry movement toward audio augmented reality (AAR). Hearing is a primary channel for sensing context, anticipating change, and navigating social space, yet AAR's everyday potential remains underexplored. We address this gap through a collaborative autoethnography (N=5, authoring) and an online survey (N=74). We identify ten roles for AAR, grouped into three categories: task- and utility-oriented, emotional and social, and perceptual collaborator. These roles are further layered with a rhythmic and embodied collaborator framing, mapping them onto micro-, meso-, and macro-rhythms of everyday life. Our analysis surfaces nuanced tensions, such as blocking distractions without erasing social presence, highlighting the need for context-aware design. This paper contributes a foundational and forward-looking framework for AAR in everyday life, providing design groundwork for systems attuned to daily routines, sensory engagement, and social expectations.

Urban HCI investigates how digital technologies shape human behaviour within the social, spatial, temporal dynamics of public space. Meanwhile, robotic furniture research demonstrates how the purposeful animation of mundane utilitarian elements can influence human behaviour in everyday contexts. Taken together, these strands highlight an untapped opportunity to investigate how animated public furniture could mediate social interaction in urban environments. In this paper, we present the design process and in-the-wild study of mobile robotic benches that reconfigure with a semi-outdoor public space. Our findings show that the gestural performance of the benches manifested three affordances perceived by passersby, they activated engagement as robots, redistributed engagement as spatial elements, and settled engagement as infrastructure. We proposed an Affordance Transition Model (ATM) describing how robotic furniture could proactively facilitate transition between these affordances to engage passersby. Our study bridges robotic furniture and urban HCI to activate human experience with the built environment purposefully.

Uncertainty is an inherent aspect of autonomous vehicle (AV) decision-making, yet it is rarely communicated to pedestrians, which hinders transparency.This study investigates how AV uncertainty can be conveyed through two approaches: explicit communication (confidence percentage displays) and implicit communication (vehicle motion cues), across different confidence levels (high and low).Through a within-subject VR experiment (N=26), we evaluated these approaches in a crossing scenario, assessing interface qualities (visibility and intuitiveness), how well the information conveyed the vehicle's level of confidence, and their impact on participants' perceived safety, trust, and user experience.Our results show that explicit communication is more effective and preferred for conveying uncertainty, enhancing safety, trust, and user experience.Conversely, implicit communication introduces ambiguity, especially when AV confidence is low.This research provides empirical insights into how uncertainty communication shapes pedestrian interpretation of AV behaviour and offer design guidance for external interfaces that integrate uncertainty as a communicative element.

Autonomous mobility systems increasingly operate in environments shared with animals, from urban pets to wildlife.However, their design has largely focused on human interaction, with limited understanding of how non-human species perceive, respond to, or are affected by these systems.Motivated by research in Animal-Computer Interaction (ACI) and more-than-human design, this study investigates animal interactions with autonomous mobility through a multi-method approach combining a scoping review (45 articles), online ethnography (39 YouTube videos and 11 Reddit discussions), and expert interviews (8 participants).Our analysis surfaces five key areas of concern: Physical Impact (e.g., collisions, failures to detect), Behavioural Effects (e.g., avoidance, stress), Accessibility Concerns (particularly for service animals), Ethics and Regulations, and Urban Disturbance.We conclude with design and policy directions aimed at supporting multispecies coexistence in the age of autonomous systems.This work underscores the importance of incorporating non-human perspectives to ensure safer, more inclusive futures for all species.

Uncertainty inherently exists in the autonomous decision-making process of robots. Involving humans in resolving this uncertainty not only helps robots mitigate it but is also crucial for improving human-robot interactions. However, in public urban spaces filled with unpredictability, robots often face heightened uncertainty without direct human collaborators. This study investigates how robots can engage bystanders for assistance in public spaces when encountering uncertainty and examines how these interactions impact bystanders' perceptions and attitudes towards robots. We designed and tested a speculative `peephole' concept that engages bystanders in resolving urban robot uncertainty. Our design is guided by considerations of non-intrusiveness and eliciting initiative in an implicit manner, considering bystanders' unique role as non-obligated participants in relation to urban robots. Drawing from field study findings, we highlight the potential of involving bystanders to mitigate urban robots' technological imperfections to both address operational challenges and foster public acceptance of urban robots. Furthermore, we offer design implications to encourage bystanders' involvement in mitigating the imperfections.

Virtual reality (VR) has been increasingly utilised as a simulation tool for human-robot interaction (HRI) studies due to its ability to facilitate fast and flexible prototyping. Despite efforts to achieve high validity in VR studies, haptic sensation, an essential sensory modality for perception and a critical factor in enhancing VR realism, is often absent from these experiments. Studying an interactive robot help-seeking scenario, we used a VR simulation with haptic gloves that provide highly realistic tactile and force feedback to examine the effects of haptic sensation on VR-based HRI. We compared participants’ sense of presence and their assessments of the robot to a traditional setup using hand controllers. Our results indicate that haptic sensation enhanced participants’ social and self-presence in VR and fostered more diverse and natural bodily engagement. Additionally, haptic sensations significantly influenced participants’ affective-related perceptions of the robot. Our study provides insights to guide HRI researchers in building VR-based simulations that better align with their study contexts and objectives.

Robots in urban environments will inevitably encounter situations beyond their capabilities (e.g., delivery robots unable to press traffic light buttons), necessitating bystander assistance. These spontaneous collaborations possess challenges distinct from traditional human-robot collaboration, requiring design investigation and tailored interaction strategies. This study investigates playful help-seeking as a strategy to encourage such bystander assistance. We compared our designed playful help-seeking concepts against two existing robot help-seeking strategies: verbal speech and emotional expression. To assess these strategies and their impact on bystanders’ experience and attitudes towards urban robots, we conducted a virtual reality evaluation study with 24 participants. Playful help-seeking enhanced people’s willingness to help robots, a tendency more pronounced in scenarios requiring greater physical effort. Verbal help-seeking was perceived less polite, raising stronger discomfort assessments. Emotional expression help-seeking elicited empathy while leading to lower cognitive trust. The triangulation of quantitative and qualitative results highlights considerations for robot help-seeking from bystanders.

As intelligent agents transition from controlled to uncontrolled environments, they face challenges that sometimes exceed their operational capabilities. In many scenarios, they rely on assistance from bystanders to overcome those challenges. Using robots that get stuck in urban settings as an example, we investigate how agents can prompt bystanders into providing assistance. We conducted four focus group sessions with 17 participants that involved bodystorming, where participants assumed the role of robots and bystander pedestrians in role-playing activities. Generating insights from both assumed robot and bystander perspectives, we were able to identify potential non-verbal help-seeking strategies (i.e., addressing bystanders, cueing intentions, and displaying emotions) and factors shaping the assistive behaviours of bystanders. Drawing on these findings, we offer design considerations for help-seeking urban robots and other agents operating in uncontrolled environments to foster casual collaboration, encompass expressiveness, align with agent social categories, and curate appropriate incentives.

The deployment of autonomous delivery robots in urban environments presents unique challenges in navigating complex traffic conditions and interacting with diverse road and sidewalk users. Effective communication between robots and road and sidewalk users is crucial to address these challenges. This study investigates real-world encounter scenarios where delivery robots and road and sidewalk users interact, seeking to understand the essential role of communication in ensuring seamless encounters. Following an online ethnography approach, we collected 117 user-generated videos from TikTok and their associated 2,067 comments. Our systematic analysis revealed several design opportunities to augment communication between delivery robots and road and sidewalk users, which include facilitating multi-party path negotiation, managing unexpected robot behaviour via transparency information, and expressing robot limitations to request human assistance. Moreover, the triangulation of video and comments analysis provides a set of design considerations to realise these opportunities. The findings contribute to understanding the operational context of delivery robots and offer insights for designing interactions with road and sidewalk users, facilitating their integration into urban spaces.

As mobile robots enter shared urban spaces, operating in close proximity to people, this raises new challenges in terms of how these robots communicate with passers-by. Following an iterative process involving expert focus groups (n=8), we designed an augmented reality concept that visualises the robot's navigation intent and the pedestrian's predicted path. To understand the impact of path visualisations on trust, sense of agency, user experience, and robot understandability, we conducted a virtual reality evaluation (n=20). We compared visualising both robot intent and pedestrian path prediction against just visualising robot intent and a baseline without augmentation. The presence of path visualisations resulted in a significant improvement of trust. Triangulation of quantitative and qualitative results further highlights the impact of pedestrian path prediction visualisation on robot understandability as it allows for exploratory interaction.