Integrating early assessment of robotic constructability into design optimization of a standalone classroom

Abstract

Multi-objective optimization can enhance design quality through performance simulation. However, ease or efficiency of construction is also important, and optimization may lead to difficult-to-build designs. Early quantification of constructability would allow designers to balance performance and construction issues. While it is difficult to quantify all factors that influence constructability, robotic construction simulations offer rich datasets to compare potential outcomes. This paper integrates constructability knowledge into early-stage design and examines the impact on multi-objective optimization. It evaluates robotic material delivery systems in constructing a standalone classroom optimized for structural, daylighting, and energy goals. When considering robotic pick and place time, the optimized designs differ, offering the opportunity to change design directions based on construction knowledge. Broader implications also become observable, as incorporating robots with higher carrying capacities reduces the structural elements and embodied carbon of optimal designs. This paper thus demonstrates benefits of incorporating robotic constructability simulation into early design optimization.