HOUSE – Habitations Organisation for hUman Settlement in Extraterrestrial Environment. an automised and performance driven framework of modular units layout generation.

Establishing permanent settlements in some astronomical bodies are raising increasing interest. During this process, one of the main challenges is to provide survival and living conditions in hostile environments where intervention and supplies from the Earth are highly complicated. In particular, it is essential to automate the design and construction processes since prompt design solutions that meet the needs of unexpected situations are vital in unknown scenarios. For instance, tectonic activities or impact of MMOD could cause new slopes, bringing site variation and compromising the settlement normal activities. This issue requires an expeditious response in adjusting the settlement's configuration to retrieve its functionalities, ensuring the mission’s success and inhabitants' safety.
The present research investigates an automatic design framework for a hypothetic extraterrestrial planetary settlement. It proposes an interactive design process for settlement's layout generation and relies on modular units realised with promising building techniques announced by Space agencies, using in-situ resources and 3D-printing strategies. The resulting challenge consists of the settlement's organisation considering its functional relationships – which means reasonably distributing functions among the settlement – and pondering the path/distance between some vertices. On the other hand, the layout organisation depends on many aspects of the site, like the geometrical information and the presence of water or other resources. These data may be subjected to variations and therefore represent dynamical input to the framework. These considerations bring to the need of an automatized and knowledge-based design process, where the crucial information can be integrated, leading to design outcomes with proper performances. The research of (near) optimal configuration has been achieved by the application of a metaheuristic algorithm and by setting appropriate goals.