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ANIMA is a platform for cooperative housing communities, employing reconfigurable hybrid panels and modular robots inspired by natural builders. These robots incrementally assemble living spaces, adapting their collaborative formations for complex tasks. With modular robotic construction systems and adaptive spatial planning algorithms, living spaces based on residents' needs and environmental changes are created. ANIMA features a hybrid of carbon-negative materials, enabling a lightweight yet durable circular economy where materials can be disassembled and recycled multiple times after their lifecycle. The robotic system uses specialised robots assembling hybrid panels with reinforcement, learning optimising reconfigurations. Agent-based algorithms negotiate and adapt layouts per multi-user requirements. Operating across multiple timescales, ANIMA's adaptive lifecycle negotiates private and communal spaces, facilitating real-time changes. It fosters human-robot coexistence, enabling constant community evolution through autonomous robotic assembly, flexible spatial reconfiguration, and algorithmic spatial optimisation.
ANIMA leverages artificial intelligence (AI) and robotics for eco-friendly, personalised spatial solutions, blending technology with community-focused sustainability. It promotes co-housing and sets a new standard in building practices.
ANIMA's main materials are cross-laminated timber (CLT) and hempcrete for their sustainability, recyclability, and CO2 absorption. CLT offers structural strength, while hempcrete provides thermal efficiency and carbon-negative benefits.
The connection system is based on a ‘Camlock mechanism’, ensuring simple and effective locking of components while allowing easy disassembly. All components can connect vertically and horizontally, creating hybrid and irregular connections.
The tile set includes CLT panels, hybrid panels, and hempcrete blocks for lightweight, durable, and CO2-absorbing construction. Parametric patterns optimise hybrid panel material distribution, blending environmental benefits with aesthetic façades.
ANIMA employs autonomous robots with coordinated precision to shape structures. These robots collaborate efficiently, using minimal movements, 3D precision, and specialised end-effectors that assemble components to form bigger structures.
Various simulations were performed in order to assess the fundamental movements, actions, and collaborative behaviours within the robotic system.
The robotic system highlights collaborative robots, emphasising a cooperative environment that enhances efficiency and task execution by focusing on streamlined and synergistic building processes.
The first training creates an open navigation system for robots to explore complex environments. The second phase uses reinforcement learning to improve decision-making, enabling robots to navigate and avoid obstacles in more diverse settings.
The final training phase emphasises open-ended learning, enabling ANIMA to continuously adapt and evolve. This ensures versatility for current tasks and future challenges, making the robotic system ready to tackle new challenges.
Research into agents' behaviours led to the classification of distinct behaviours, like clustering or scattering. This categorisation optimises task deployment and ensures functional and responsive spatial configurations align with the design goals.
The spatial planner algorithm uses dynamic, autonomous agents to actively generate and define spaces, playing a crucial role in shaping 3D spatial layouts within the environment.
The spatial assembly algorithm collaborates with the spatial planner to transform defined areas into complex structures. Its purpose is to place and connect components to shape the space purposefully.
The platform performs a year-round analysis to assess environmental factors like wind, sun exposure, and accessibility. It ensures a comprehensive understanding of the site by considering seasonal and long-term trends before construction.
After the site analysis is complete, ANIMA's platform introduces agents representing users' needs into the site. These agents, with distinct attributes, ensure the design meets specific requirements.
With the planning mask finalised, construction begins, using timber and hempcrete adapted to seasonal changes. In warmer months, sunlight boosts hempcrete's carbonation and timber's drying, optimising environmental benefits.