unit-code
Diffusive Habitats is a resilient architectural system that builds upon the juncture of distributed robotics, reinforcement learning, and digital platforms to reimagine the way we conceive and inhabit architecture. Challenging traditional praxis, the project is conceived under the premise of constant spatial reconfiguration, non-linear life cycles, and distributed ownership. And thus, via the interplay of its algorithmic, mechatronic, and material research, Diffusive Habitats critically explores the idea of a living architectural system capable of self-assessment, organisation, and improvement.
The project is best understood and explained through four primary episodes of engagement; setup and design; fabrication and assembly; inhabitation; and migration and adaptation. These four chapters illustrate all necessary steps of designing, configuring, and inhabiting architectural systems. The first two sections focus on initiating and configuring initial architectural spaces. The latter two, investigate the notion of change and adaptation, which are fundamental to the system's resilience and overall disruptive architectural exploration.
Diffusive Habitats is a comprehensive architectural system that utilises reinforcement learning, AI, and robotic assembly. The case study illustrates the holistic process and provides situated scenarios to show the potential of the system.
The Spatial Planner Algorithm starts off Diffusive Habitat’s algorithmic process. Within it, individual spaces grow and negotiate to optimise space under a series of situated conditions.
To encourage collaboration, the agents are trained to carry out specific tasks using a weighted reward system.
Spatial assembly physically renders the result of spatial planner. Utilising various techniques found in procedural generation algorithms, spatial assembly manipulates the curated tile set to solve for the constraints given by the spatial planner.
Various versions of the primary units have been designed to solve specific conditions found within the system. These custom units include: MEP services, solar panels, surface charging, multi-material, and adaptable storefront units.
Material prototyping has played an instrumental role in the design and robotic testing process. Frequent alterations and modifications have considered many factors, for example the weight, stability, and size.
Diffusive Habitats’ mechatronic design was conceived by analysing, merging, challenging, and furthering state-of-the-art robotic morphologies. At its core, the design pursues simplicity and collaboration, while minimising motor forces and torques.
Systematic experimentation (gauging the capabilities and limitations of the robotic prototypes) proved fundamental for prototype evolution, revealing the vast flexibility and unforeseen capabilities of collaborative behaviours.
Iterative studies on robotic control led to reactive 3D-tracking with Unity and Optitrack. With it, Diffusive Habitats is able to motion-capture and coordinate multiple robots in real-time, while receiving precise positioning feedback data.
The project utilises a game-based research framework to develop its robotic intelligence. This arena illustrates the process by which AI is trained to compete against humans and hardcoded algorithms within that framework.
The framework’s best performing strategies can be applied to larger scale reconfigurations. For instance, this 6-robot simulation features AI-based pass behaviors, pathfinding algorithm sequences, and human-derived multi-agent “turn” coordination.
Likewise, this intelligence can be applied to the project’s physical prototypes and physical studies.
Given the nature and flexibility of Diffusive Habitats' system, material can be reconfigured into an array of shapes to serve diverse functions and account for changing needs.
Physical reconfiguration studies gauge constraints and inform the computational models. For instance, this 50-unit arch could not be assembled as initially calculated, revealing much about the sequencing and reinforcement of cantilevering structures.
Diffusive Habitats engages in improvisational, action-centric, and situated activity. The temporal nature of the structure allows for various readings across multiple scales of time.
Any given configuration can be interpreted as a result of negotiations between multiple agents. In the case of primary living spaces, the occupants have a direct connection with the architecture's configuration.
Larger configurations decided by the community reflect a multitude of agents and time. The changes are caused by and effect inhabitants collectively; changes on this scale might be described as seasonal or regular.
The urban scale is still fundamentally shaped in an ad hoc fashion. However, at this scale, the result conveys a much larger succession of moments in time.
The primary actions of the robots revolve around reconfiguring material, robotic choreography and dance studies, as well as interactions between human and non-human agents.