The International Association for Automation and Robotics in Construction
Publications / CCC 2025 - Zadar, Croatia
ROBOTIC SYSTEMS FOR AUTONOMOUS DATA ACQUISITION IN CONSTRUCTION: A CASE STUDY
Traditional data acquisition methods in construction often struggle with accuracy, efficiency, and adaptability, especially in dynamic jobsite conditions. These shortcomings can lead to elevated error rates, schedule overruns, and increased resource consumption. To address these issues, this paper presents the development of an autonomous robotic system that synergizes Simultaneous Localization and Mapping (SLAM), autonomous exploration, and robust data handling algorithms for enhanced reality capture and reduced human involvement. Building upon state-of-the-art SLAM solutions, our approach leverages LiDAR-based 3D mapping to enable real-time environment reconstruction, while an autonomous exploration algorithm guides the robot through unknown areas. A semi-autonomous robotic platform was deployed and tested in an active construction environment. By integrating a relational database framework and low-latency communication protocols, the platform efficiently handles large volumes of sensor data, facilitating both immediate oversight and post-processing analysis. Preliminary results indicate that the system adapts effectively to shifting on-site conditions, providing comprehensive and timely data that enhances project management and decision-making processes. This research highlights the value of autonomous robotic solutions as a cornerstone of the emerging Construction 4.0 paradigm, offering a roadmap for more sustainable, efficient, and data-driven operations.