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

即兴创作 手势 人机交互 计算机科学 建筑工程 沟通 工程类 心理学 视觉艺术 艺术 人工智能
作者
Alex Binh Vinh Duc Nguyen,Jan Leusmann,Sven Mayer,Andrew Vande Moere
出处
期刊:Cornell University - arXiv
标识
DOI:10.48550/arxiv.2501.01813
摘要

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.

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