Progress monitoring in the construction industry is mostly a manual process through in-person visual inspection and it leads to inconsistent, time-consuming, labor-intensive, and error-prone data acquisition. The key in progress monitoring is accurate, timely, and regular data collection and analysis during the construction process. Automating the process of regular data collection in progress monitoring can enable systematic recording of construction progress. To achieve this goal, mobile robots with autonomous navigation and high-performance locomotion capabilities can potentially navigate dynamically changing construction workspaces to perform regular data collection. This study identifies fundamentals of robot-enabled procedures for automated construction progress monitoring and explores the opportunities and challenges of utilizing a legged robot in this process. Through collaboration between academia and industry, this study conducts a set of experiments with a four-legged robot equipped with a 360° image capture technology to automate data collection in construction progress monitoring. The results of these experiments have identified the opportunities and operating procedure for robot-enabled image capturing. The study has also discussed current limitations in the automated construction progress monitoring including safety limitations, operation limitations, and mission limitations.