@inproceedings{f45f2b7f21a34cd8a301b9123ffc2f24,
title = "A Human–Machine Collaborative Building Spatial Layout Workflow Based on Spatial Adjacency Simulation",
abstract = "The space layout of a reasonable modular building prototype is a time consuming and complex process. Many studies have optimised automatic spatial layouts based on spatial adjacency simulation. Although machine-produced plans satisfy the adjacency and area constraints, people still need further manual modifications to meet other spatially complex design requirements. Motivated by this, we provide a human–machine collaborative design workflow that simulates the spatial adjacency relationship based on physical models. Compared with previous works, our workflow enhances the automated space layout process by allowing designers to use environment anchors to make decisions in automatic layout iterations. A case study is proposed to demonstrate that the solution generated by our workflow can initially complete different customised design tasks. The workflow combines the advantages of the designer's decision-making experience in manual modelling with the machine's ability in rapid automated layout. In the future, it has the potential to be developed into a designer-machine collaboration tool for completing complex building design tasks.",
keywords = "Spatial adjacency simulation, Physical model, Responsive design process, Human–machine collaborative workflow, · Real-time visualization",
author = "Ximing Zhong and Fujia Yu and Beichen Xu",
year = "2023",
month = apr,
day = "4",
doi = "10.1007/978-981-19-8637-6_2",
language = "English",
isbn = "978-981-19-8636-9",
series = "Computational Design and Robotic Fabrication",
publisher = "Springer",
pages = "14--24",
editor = "Yuan, {Philip F.} and Hua Chai and Chao Yan and Keke Li and Tongyue Sun",
booktitle = "Hybrid Intelligence",
edition = "1",
note = "International Conference on Computational Design and Robotic Fabrication, CDRF ; Conference date: 27-06-2022 Through 05-07-2022",
}