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Main Authors: Ji, Ruochen, Tiangang, Lyu
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2506.06066
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author Ji, Ruochen
Tiangang, Lyu
author_facet Ji, Ruochen
Tiangang, Lyu
contents Mixed reality (MR) environments offer embodied spatial interaction, providing intuitive 3D manipulation capabilities that enhance the conceptual design process. Parametric modeling, a powerful and advanced architectural design method, enables the generation of complex, optimized geometries. However, its integration into MR environments remains limited due to precision constraints and unsuitable input modalities. Existing MR tools prioritize spatial interaction but lack the control and expressiveness required for parametric workflows, particularly for designers without formal programming backgrounds. We address this gap by introducing a novel conversational MR interface that combines speech input, gesture recognition, and a multi-agent large language model (LLM) system to support intuitive parametric modeling. Our system dynamically manages parameter states, resolves ambiguous commands through conversation and contextual prompting, and enables real-time model manipulation within immersive environments. We demonstrate how this approach reduces cognitive and operational barriers in early-stage design tasks, allowing users to refine and explore their design space. This work expands the role of MR to a generative design platform, supporting programmatic thinking in design tasks through natural, embodied interaction.
format Preprint
id arxiv_https___arxiv_org_abs_2506_06066
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Conversational Interfaces for Parametric Conceptual Architectural Design: Integrating Mixed Reality with LLM-driven Interaction
Ji, Ruochen
Tiangang, Lyu
Human-Computer Interaction
Mixed reality (MR) environments offer embodied spatial interaction, providing intuitive 3D manipulation capabilities that enhance the conceptual design process. Parametric modeling, a powerful and advanced architectural design method, enables the generation of complex, optimized geometries. However, its integration into MR environments remains limited due to precision constraints and unsuitable input modalities. Existing MR tools prioritize spatial interaction but lack the control and expressiveness required for parametric workflows, particularly for designers without formal programming backgrounds. We address this gap by introducing a novel conversational MR interface that combines speech input, gesture recognition, and a multi-agent large language model (LLM) system to support intuitive parametric modeling. Our system dynamically manages parameter states, resolves ambiguous commands through conversation and contextual prompting, and enables real-time model manipulation within immersive environments. We demonstrate how this approach reduces cognitive and operational barriers in early-stage design tasks, allowing users to refine and explore their design space. This work expands the role of MR to a generative design platform, supporting programmatic thinking in design tasks through natural, embodied interaction.
title Conversational Interfaces for Parametric Conceptual Architectural Design: Integrating Mixed Reality with LLM-driven Interaction
topic Human-Computer Interaction
url https://arxiv.org/abs/2506.06066