For the digital transformation of the construction industry, mobile data collection equipment is being widely used to acquire on-site data more efficiently. Although Path Planning optimization is crucial for the effective use of such devices, existing research has largely focused on UAV path optimization, leaving UGV path planning relatively underexplored. Furthermore, due to the complex and dynamic nature of actual construction sites, manual operation remains common, which may lower data collection efficiency. This study proposes an optimal path planning methodology that reflects the unique characteristics of construction sites and UGV to enhance data collection efficiency. Utilizing a 2D grid-based site model, the proposed approach differentiates between accessible and inaccessible areas and optimizes data collection routes based on site-specific conditions. By addressing the limitations of current UGV route planning methods, this research presents a framework for improving both the effectiveness and accuracy of data collection in complex, dynamic construction environments.
