Sergio Mutis 嘅作品 Diffusive Habitats 可重構建築系統

由設計師 Sergio Mutis 創作嘅 Diffusive Habitats 可重構建築系統係備受推崇嘅 2023 A' Design Award 銅獎得獎作品，獲獎類別為生成式設計。

銅生成式· 2023

Diffusive Habitats 可重構建築系統

由 Sergio Mutis

生成式類別嘅 A' Design Award 銅獎得獎者

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驗證設計 #145846 嘅獲獎狀態

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色彩

設計

關於 Diffusive Habitats 可重構建築系統

《瀰漫棲居》係一個建築系統,結合分散式機械人技術、強化學習同一個線上平台,令空間可以隨時間推移而重新配置。機械人單元會移動模組化組件,從而改變棲息空間嘅佈局。呢啲模組化組件由CNC銑削夾板製成,並內嵌3D打印連接介面。機械人原型則以回收塑膠3D打印而成。呢個平台會根據住戶需求、結構完整性同環境表現嚟組織空間。其目標係減少拆卸工程,令居所更具彈性。

榮譽認可

關於A' Design Award 銅獎

Diffusive Habitats 可重構建築系統是 A' Design Award 銅獎得主，這是授予以創造力、獨創性和敏銳見長的傑出設計的極具聲望的認可。銅獎得主是技藝嫻熟、創意驚人的作品，印證了其設計師豐富的經驗、想像力與機智。預計Diffusive Habitats 可重構建築系統將成為一件備受推崇、令人欽佩且被珍愛的物品，兼具顯著的專業性與創新性。這件贏得 A' Design Award 銅獎的設計融入藝術、科學、設計和技術領域的最佳實踐，並因注重細節而出類拔萃。Diffusive Habitats 可重構建築系統出色地滿足需求，觸動渴望，迷住情感，並吸引好奇心。

設計背後

新聞資料包

由設計師提供嘅製作人員名單、團隊成員同技術詳情。

獨特屬性: Diffusive Habitats (DH) is a resilient architectural system that builds upon the juncture of distributed robotics, reinforcement learning, and digital platforms to reimagine the way architecture is conceived and inhabited. Challenging traditional praxis, the project embraces constant spatial reconfiguration and distributed ownership. And, via the interplay of applied transdisciplinary research, DH critically explores a spatial system capable of self-assessment, organization, and improvement.
尺寸同包裝: Robot Prototypes 3.0.
Dimensions: Width 100mm x Depth 100mm x Height 280mm.
Composition: 3D-Printed recycled plastic (PLA). Weight: 420g. Parts: 5 links of 3D-printed PLA, 8 neodymium magnets 20dx3, 4 Dynamixel AX-12A motors, 1 LiPo 3cell Battery, 1 U2D2 Power Hub, 1 Raspberry Pi Zero.

// Material Prototypes 3.0.
Standard Dimensions: Width 140mm x Depth 420mm x Height 140mm. Standard Weight: 477g.
Composition: CNC-milled laminated plywood with embedded 3D-printed PLA connection interfaces.
標籤: Living Architecture, Distributed Mechatronics, Reinforcement Learning, Multi-Agent Systems, Generative Architecture
生產技術: The DH system consists of multiple correlated elements that were heuristically prototyped, tested, and redesigned. Its space generation platform was scripted in C-sharp for Unity3D with the ML Agents U3D reinforcement learning framework. Laminated plywood prototypes were CNC-milled and assembled with friction joints. 3D-printed PLA robotic prototypes were developed with a Unity3D digital twin environment, wireless Raspberry Pi communication, Dynamixel AX-12A motors, and Optitrack motion capture.
設計挑戰: Besides technological and transdisciplinary challenges, the shift in authorship paradigm was perhaps the greatest obstacle in the development of the project. Rather than the desires of individual designers, this research required a heuristic process of trial and error, where the design was the result of cascading iterations of parameter optimization. Once the team embraced that fundamental idea, the once slow and erratic project advanced swiftly beyond its initial research objectives.
研究: Diffusive Habitats employs systematic heuristic research, with reinforcement learning and self-play frameworks for intelligence development. The main research objective was to explore an architectural system capable of self-organization, assessment, and improvement, that would embrace technological advancements to reimagine how we conceive and inhabit spaces. To do so, the project adopted a method of small attainable mechatronic, computational, material, and intelligence milestones that were quickly designed, tested, and analyzed to inform an upcoming iteration. Data collection and analysis included: weight, task success rate, and cost for robotic design / multi-requirement satisfaction for computational generative design / weight, open source fabrication index, and sustainability for material research / task success rate, speed, and energetic efficiency for robotic intelligence. Tests were carried out via simulations in Unity and C# for computational algorithms and robotic intelligence, and via physical tests for mechatronic and material development. Initial results were systematically improved by following iterations leading up to a mechatronic design with diverse capabilities (particularly while collaborating), a computational framework that could organize space under numerous requirements far better than any one designer, a material unit that proved capable of forming multiform structures (though not yet capable of being employed in buildings over 2 stories high), and a robotic intelligence that could calculate, optimize, and execute large reconfiguration tasks.

The project still requires development to be thoroughly applied in architectural practice. Yet, within the constraints of a 1-year Master's degree project, it was considered a vast success and will be used to attract interest and funds to further the research. The effects of this investigation range from avoiding demolition and boosting the sustainability of the built environment, to transforming rigid urban dwellings into flexible hubs for the ever-accelerating change of our times. Altogether, this research explores a radically novel way of living that could be a widespread reality in the future, or allow for new conversations to occur that will ultimately improve the way we live.
靈感: Unlike other crafts, arts, and industries, architecture has not seen significant developments during the upheaval of the digital revolution. Traditional praxis continues to produce buildings incapable of substantial programmatic flexibility, that become obsolete within the ever-accelerating change of the times, and quickly end up in queue for demolition. Diffusive Habitats challenges this unsustainable practice, instrumentalizing its technological juncture in the lookout for renewed solutions.
項目時長: The project was developed as part of the Architectural Design M.Arch. at UCL in London, UK. It started in 2021 and culminated in late 2022 at Bartlett B-Pro Show Expo, where it received the Bartlett AD Gold Medal. The case-study is located in Brixton, London, and the design team comes from India, Colombia, the US, and Greece.
操作流程: Diffusive Habitats operates via an online platform facilitating plot search, habitat crowdfunding, collaborative design, and spatial reconfiguration. Behind its intuitive interface, the platform employs sophisticated algorithms to organize space based on inhabitant requirements, structural integrity, and environmental optimization. With it, a community is able to design their ideal habitat, see it constructed by robots, and adjust it to account for changing individual and collective needs.
團隊成員: Sergio Mutis
Eric Hughes
Faizunsha Ibrahim Ghousiaa
Garyfallia Papoutsi.
圖片來源: Image #1: Creator Eric Hughes, DH Little Girl Rendering, 2022
Image #2: Creator Sergio Mutis, DH Reinforcement Training Arena, 2022
Image #3: Creator Eric Hughes, DH Skylight Rendering, 2022
Image #4: Creator Sergio Mutis, DH Robotic Reconfiguration Studies, 2022
Image #5: Creator Eric Hughes, DH Speculative Urbanism, 2022