Geometric Feedback System for Robotic Spraying

Abstract

In this paper, we tackle the task of replacing labor intensive and repetitive manual inspection of sprayed concrete elements with a sensor-based and automated alternative. We present a geometric feedback system that is integrated within a robotic setup and includes a set of depth cameras used for acquiring data on sprayed concrete structures, during and after fabrication. The acquired data are analyzed in terms of thickness and surface quality, with both sets of information then used within the adaptive fabrication process. The thickness evaluation is based on the comparison of the as-built state to a previous as-built state or to the design model. The surface quality evaluation is based on the local analysis of 3D geometric and intensity features. These features are used by a random forest classifier trained using data manually labelled by a skilled professional. With this approach, we are able to achieve a prediction accuracy of 87 % or better when distinguishing different surface quality types on flat specimens, and 75 % when applied in a full production setting with wet and non-planar surfaces. The presented approach is a contribution towards in-line material thickness and surface quality inspection within digital fabrication.