An image convolution-based method for the irregular stone packing problem in masonry wall construction

The use of natural stones as building material can help reducing the carbon footprint of the construction industry. However, their non-uniform shapes makes the construction of stone masonry structures challenging. Therefore, the development of efficient algorithms for the stacking of irregular stones obeying structural and architectonic requirements is essential. In this paper, we propose an image-based method for automating the stacking of non-uniform stones in the construction of 2D load-resistant stone masonry walls. Stone wedging, a traditional technique employed by skilled masons, is implemented to reinforce the stability of stone placements. We use image processing for accelerating the stone selection and placement, and determine the wall's resistance using a variational rigid-block modeling approach. It is demonstrated that the developed method is efficient and robust in challenging conditions. The analysis of the computational performance of the presented method shows that it is suitable for automated construction.