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.

Although intended to foster spontaneous interactions among workers, a typical open-plan office layout cannot mitigate visual, acoustic, or privacy-related distractions that originate from unplanned meetings. As office workers often refrain from tackling these issues by manually demarcating or physically relocating to a more suitable subspace that is enclosed by movable partitions, we hypothesise that these subspaces could instead be robotically manifested. This study therefore evaluated the perceived impact of two mobile robotic partitions that were wizarded to jointly manifest an enclosed subspace, to: 1) either `mitigate' or `intervene' in the distractions caused by spontaneous face-to-face or remote meetings; or 2) either `gesturally' or `spatially' nudge a distraction-causing worker to relocate. Our findings suggest how robotic furniture should interact with office workers with and through transient space, and autonomously balance the distractions not only for each individual worker but also for multiple workers sharing the same workspace.

Cross-Reality Transitional Interfaces support tasks that require interactions at different levels of virtuality. However, there is little knowledge on how such capabilities can be scaled on vertical and life-sized surfaces, by offering haptic feedback, transitioning the surface between physical and virtual environments, and moving the surface at room-scale. The aim of our study is to generate an empirical understanding of which combinations of mixed reality and a user-controlled movable robotic surface (resulting in four virtuality levels) are better suited to execute five tasks, which differed in terms of haptic feedback. During our user study (N=24), physical environment-physical surface was used most due to its familiarity and haptic feedback, while the virtual environment mode was experienced as more relaxing and fun, and the virtual surface mode as more convenient and safer.