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

TL;DR

This study explores how robotic furniture can use spatial gestures to communicate architectural intents, involving expert co-design sessions, motion analysis, and categorization of gestural strategies to enhance interpretability.

Contribution

It introduces architectonic gestures as a new form of robotic communication in adaptive architecture, bridging HRI and Human-Building Interaction research.

Findings

Identified 20 unique gestural strategies for conveying architectural intents.

Developed a categorization of gestures based on spatial impact and motion.

Proposed architectonic gestures as a novel communication method for robotic furniture.

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.