AR-Assisted Assembly in Self-Build Construction with Discrete Components

Abstract

The prevailing issue of low housing supply is caused in part by a lack of skilled construction workers. If unskilled residents were adequately equipped, they could potentially address this issue, expanding and adapting their homes without professional builders and designers. This research proposes the use of discrete components to build on unused community lands using augmented reality (AR) assisted assembly. Enfield, a low-density community in London, was chosen as the case study location. Modular components, pre-assembled off-site by robots, were designed to form a set of interlocking structures making them easy to install and dismantle. ARassisted construction integrates design and construction processes, helping to resolve sequencing and flow issues during assembly. A robotic simulator was used to visualise the robotic assembly process and an AR programming was used to guide self-builders with no building experience through assembly. An experiment was set up, where AR-assisted non-professionals use modular components to assemble a 1:2 scale pavilion model. This workflow could encourage individual and community-led building expansions and could be effective in reducing pressure on the construction industry and providing more housing.