Development of a 2D SLAM based radiation mapping system for surface contamination measurement

This study developed a SLAM-based radiation measurement system using an autonomous mobile robot and a LiDAR sensor to improve the quantitative accuracy of surface contamination assessments. Conventional fixed or manually operated radiation detection systems have limitations in performing precise evaluations over wide areas. To resolve these issues, the proposed system integrates autonomous navigation, real-time localization, and dynamic measurement correction. Correction factors derived from static experiments are applied in real time to compensate for CPS errors caused by variations in detector height and speed, enabling accurate measurements under various conditions. Scanning experiments were conducted using Co-60 radiation sources. After applying the correction factors, the average deviation was reduced to within 10%, with lower scanning speeds resulting in further error reduction. This system, equipped with a real-time correction algorithm, serves as a foundational technology for dynamic radiation mapping and has potential applications in facility decommissioning and precision measurement of radioactive contamination areas.