Eliciting Understandable Architectonic Gestures for Robotic Furniture through Co-Design Improvisation

TL;DR

The paper investigates how adaptive architecture can communicate autonomous intents to occupants using gestures from a mobile robotic partition. It employs a co-design improvisation with 15 multidisciplinary experts to elicit gestures for six intents, analyzed via motion-tracking, a Laban-based questionnaire, and thematic analysis. The study identifies 20 gestural strategies, introducing architectonic gestures as a novel, spatially indexical approach that complements deictic and emblematic gestures. The findings bridge human-robot interaction (HRI) and human-building interaction (HBI), offering a design framework to improve the legibility and acceptance of robotic furniture in interior spaces, with implications for safer, more intuitive adaptive environments.

Abstract

The vision of adaptive architecture proposes that robotic technologies could enable interior spaces to physically transform in a bidirectional interaction with occupants. Yet, it is still unknown how this interaction could unfold in an understandable way. Inspired by HRI studies where robotic furniture gestured intents to occupants by deliberately positioning or moving in space, we hypothesise that adaptive architecture could also convey intents through gestures performed by a mobile robotic partition. To explore this design space, we invited 15 multidisciplinary experts to join co-design improvisation sessions, where they manually manoeuvred a deactivated robotic partition to design gestures conveying six architectural intents that varied in purpose and urgency. Using a gesture elicitation method alongside motion-tracking data, a Laban-based questionnaire, and thematic analysis, we identified 20 unique gestural strategies. Through categorisation, we introduced architectonic gestures as a novel strategy for robotic furniture to convey intent by indexically leveraging its spatial impact, complementing the established deictic and emblematic gestures. Our study thus represents an exploratory step toward making the autonomous gestures of adaptive architecture more legible. By understanding how robotic gestures are interpreted based not only on their motion but also on their spatial impact, we contribute to bridging HRI with Human-Building Interaction research.

Figures (4)

• Figure 1: The questionnaire used to elicit experts in differentiating their own designed gestures, with the order of measures randomised for each expert.
• Figure 2: The questionnaire results of 15 experts evaluating their 90 designed gestures across eight measures. The gestures were categorised into five groups based on the dimensions of purpose (informing versus nudging) and urgency (non-urgent versus urgent), along with control gestures.
• Figure 3: The three gestural strategies that were most frequently designed for each of the six intents (see \ref{['tab:intent']}), together with their occurrence scores (%), showing how 'nudging' intents often required gestural sequences that combined multiple gestural strategies (see \ref{['tab:patterns']}) more than other intents.
• Figure 4: Our experts viewed architectonic gestures as indexically referencing the spatial impact of the partition to convey intent, semiotically distinguishing them from iconographic deictic gestures and symbolic emblematic gestures.