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Stigmergic Spaces

Project details

Programme

Cluster RC3

Year 1

This project introduces a ground-breaking approach to space planning through a multi-agent strategy, underpinned by a powerful algorithmic framework. This innovative concept envisions a dynamic space where programmable collective intelligence thrives, shaping its own evolution. Drawing inspiration from nature’s social organisms like ants, termites, and slime moulds, renowned for their self-organising capabilities, the project ingeniously adapts these principles.

By harnessing these biological mechanisms, Stigmergic Spaces addresses the intricate spatial relationships among diverse programmatic elements. The final spatial arrangement emerges from a competitive ecology, reminiscent of natural ecosystems, enabling the resolution of intricate design challenges with conflicting demands. This approach offers a paradigm shift, moving beyond traditional design methodologies, and embraces a self-guided, responsive design process, ultimately producing spaces that possess a dynamic and adaptable character.

Students

About Stigmergic Spaces

Background

Stigmergic Spaces leverages robots and intelligent systems to enhance land accessibility. The project addresses environmental challenges, particularly in rugged and inaccessible locations, where housing construction is often restricted.

Studying Nature

Stigmergic Spaces draws inspiration from nature, highlighting the connection between stability, collective intelligence, collaboration and optimisation; and demonstrating how biological behaviours offer solutions for real-world challenges.

Stigmergic Spaces System

In Stigmergic Spaces, three systems intertwine: the robotic system coordinates material assembly based on simulation guidance, which in turn, integrates mechanics and environmental feedback for improved robot motion and composition.

Material System

Material System Overview

Exploring construction systems yields diverse geometries, prioritising stability, load-bearing capacity, and functionality. Through iterations, these approaches aim to redefine architectural expression and expand building possibilities.

Material System Aggregation

The incorporation of mitred corners into a component presents a distinct advantage by negating the necessity to address individual nodes, thereby affording heightened flexibility in the creation of intricate and organically fluid forms.

Material System Joint Details

In joint design, a power source with positive and negative pole is employed to ensure uninterrupted component aggregations with precise alignment. Moreover, establishing exact connection entails precise positioning, often overseen by robots.

Robotic Research

Robotic Research Overview

Robotic System Workflow

The development of robots is built on the foundation of components' shapes and splicing logic. Stigmergic Spaces focuses on incorporating the movement of the sliding rail robot and the rotary arm.

Robotic Testing: Basic Movement

Physical testing is vital to ensure the robot's practicality in construction. Sizing adjustments, especially for delivery and collaboration, were made iteratively until reaching the desired scale.

Robotic Testing: Cooperation

The use of multiple robots can occur horizontally or vertically, enabling the accomplishment of tasks that would be challenging for a single robot alone. This approach also increases the robot's load-carrying capacity and radius of activity.

Algorithm Research: Spatial Planning

Spatial Planning: Algorithm Overview

The spatial planner enables the analysis of relationships between various objects by synthesising data about the location, size, and use of different components into a spatial map.

Plan Configuration Algorithm

This algorithm extracts data structures that encapsulate the essence of various spaces. Thorough assembly and analysis of these data structures an image showing the connectivity between spatial elements or neighbours is yielded.

User Oriented Planning Algorithm

User positions correspond to nodes in the grid, and the spatial extent of location-based generation adapts over time and in response to user demand. Once user requirements are being uploaded, spatial data is reprogrammed for alignment.

Plan Reconfiguration Algorithm

Within this graphic construct, each node signifies a distinct functional area, while the edges interlinking these nodes denote the spatial relationships and adjacency between these spaces.

Algorithm Research: Force Feedback System

Force Feedback System Overview

Decentralisation in Stigmergic Spaces denotes the distributed and adaptable nature of structural configuration and reconfiguration. Real-time evaluation and adjustment, inspired by non-human creatures, ensures stability in unpredictable terrains.

Aggregation Sequence

The simulation environment plays a pivotal role in comprehensively analysing growth dynamics, encompassing both disordered and rule-based processes, thereby enriching our understanding of diverse growth mechanisms.

Architectureal Components

A process of analysis considers structures with varying module counts, corners and extensions. These structures own datasets rich in information, including force states and torque values, with significant implications for architectural scenarios.

Systematic Feedback

The controller operates in a systematic manner, harnessing the insights gained from force feedback. By continuously detecting the building sequence based on force dynamics during the growth process, the system ensures overall stability.

Adaptational Architectural Scenario

Adaptational Architectural Scenario Overview

A cluster optimisation algorithm secures optimal build paths, keeping the robot's build process integrated in a changing terrain. This algorithm finds applications in real construction contexts, from bridge to individual homes to collective housing.

Bridge Structure

Individual

Collective

Spatial Prototype

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The Bartlett
B-Pro Show 2023

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