LAUSR

Abstract To increase the degree of automation and frequency of data collection for monitoring construction sites, there has been a rapid increase in the number of studies, in the past few years, that developed and/or examined mobile robotic applications in construction. These vision-based platforms capable of autonomous navigation and scene understanding are becoming essential in many construction applications, namely construction sites surveying, work-in-progress monitoring, and existing structure inspection. Simultaneous Localization and Mapping (SLAM) and object recognition for proper context-aware motion planning are some of the core vision techniques that are driving innovation for these robotic systems. To characterize the limitations of current techniques on real-time performance and identify challenges in integration and implementation for construction applications, this paper proposes a mobile robotic platform that incorporates a stack of embedded platforms with integrated Graphical Processing Units (GPUs). This paper presents three case studies to evaluate the performance of the proposed system. The results demonstrate the robustness and feasibility of developing and deploying an autonomous system in the near future.