Diffusive Habitats Gaýtadan Sazlanyp Bilinýän Binagärlik Ulgamy by Sergio Mutis

Diffusive Habitats Gaýtadan Sazlanyp Bilinýän Binagärlik Ulgamy by Sergio Mutis is a highly esteemed winner of the very prestigious 2023 A' Design Award Bürünç Baýragy in Generatiw, Algoritmik, Parametrik we AI Goldawly Dizaýn Competition Category.

BürünçGeneratiw· 2023

Diffusive Habitats Gaýtadan Sazlanyp Bilinýän Binagärlik Ulgamy

by Sergio Mutis

A' Design Award Bürünç Baýragy Winner in Generatiw Category

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The Design

About Diffusive Habitats Gaýtadan Sazlanyp Bilinýän Binagärlik Ulgamy

Diffusive Habitats — bu paýlanan robototehnikany, güýçlendirilen öwrenişi we onlaýn platformany utgaşdyrýan binagärlik ulgamy bolup, giňişlikleriň wagtyň geçmegi bilen gaýtadan sazlanmagyna mümkinçilik berýär. Robot enjamlary ýaşaýyş jaýynyň meýilnamasyny üýtgetmek üçin modul bölekleri hereket etdirýär. Modul bölekler CNK-de işlenen köp gatlakly faneradan ýasalyp, olaryň içine 3D-çap edilen birleşdiriji interfeýslar ornaşdyrylandyr. Robot prototipleri gaýtadan işlenen plastmassadan 3D-çap arkaly taýýarlanylýar. Platforma ýaşaýjylaryň talaplaryna, gurluşyk berkligine we daşky gurşaw netijeliligine laýyklykda giňişligi guraýar. Maksat — ýumurmak işlerini azaltmak we ýaşaýyş jaýlaryny has çeýe etmekdir.

The Recognition

About the A' Design Award Bürünç Baýragy

Diffusive Habitats Gaýtadan Sazlanyp Bilinýän Binagärlik Ulgamy A' Design Award Bürünç Baýragynyň ýeňijisidir; bu döredijilik, ussatlyk we ýiti akyl bilen tapawutlanýan tapawutly dizaýnlara berilýän aşa abraýly ykrarnamadyr. Bürünç ýeňijileri dizaýnerleriniň giň tejribesini, hyýalyny we tapawutlylygyny tassyklaýan örän ussat we geň galdyryjy derejede döredijilikli eserlerdir. Diffusive Habitats Gaýtadan Sazlanyp Bilinýän Binagärlik Ulgamy uly baha berilýän, haýran galynýan we söýülýän, üns çekiji derejede hünärmenlikli we täzelikçi zat bolmagy garaşylýar. A' Design Award Bürünç Baýragyny gazanan bu dizaýn sungatda, ylymda, dizaýnda we tehnologiýada iň oňat tejribeleri öz içine alýar we jikme-jiklige edýän üni bilen ajaýypdyr. Diffusive Habitats Gaýtadan Sazlanyp Bilinýän Binagärlik Ulgamy zerurlyklary ajaýyp derejede kanagatlandyrýar, isleglere degýär, duýgulary özüne çekýär we gyzyklanmany çekýär.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: 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.
Dimensions & Packaging: 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.
Tags: Living Architecture, Distributed Mechatronics, Reinforcement Learning, Multi-Agent Systems, Generative Architecture
Production Technology: 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.
Design Challenge: 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.
Research: 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.
Inspiration: 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.
Project Duration: 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.
Operation Flow: 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.
Team Members: Sergio Mutis
Eric Hughes
Faizunsha Ibrahim Ghousiaa
Garyfallia Papoutsi.
Image Credits: 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