The International Association for Automation and Robotics in Construction
Publications / 2025 Proceedings of the 42nd ISARC, Montreal, Canada
Real-time 3D Perception System of Construction Equipment for Autonomous Mobile Robots
Automation using mobile robots at construction sites is gaining attention as a key technology to enhance productivity and safety. However, due to the unstructured nature of construction sites with dynamic elements like construction equipment, robots must perceive their positions and movements in real-time to adapt to workflow changes while performing tasks. To address this issue, this paper proposes a system that enables mobile robots to detect the spatial positions of construction equipment in real time. The system integrates a voxel-based deep learning detection model with a Simultaneous Localization and Mapping (SLAM) algorithm, allowing real-time detection of construction equipment within a consistent reference coordinate system using 3D point cloud data collected by the mobile LiDAR. Experimental results demonstrate that the system achieves an average detection accuracy of 74.51% (AP@R40, IoU 0.25) for excavators, dump trucks, graders, and rollers, demonstrating its capability to accurately recognize the spatial information of construction equipment. This approach highlights the potential for mobile robots to effectively perceive construction equipment in active construction sites, enabling safer and more efficient task execution.
