Development and Testing of a Semi-automated Multimodal Radiation Detection System

Radiation mapping of large areas with high radiation doses can result in significant dose acquisition to workers in emergency response and national security applications. In this regard, innovative solutions are always sought to mitigate large doses and simultaneously provide contextual information of the scene under surveillance. In this work, we built a cost-effective semi-automated multimodal radiation detection system, which employs multiple sensors: radiation detector, optical/thermal imaging camera, and Light Detection and Ranging (LiDAR). The integration of multiple sensors provides information that is unavailable via conventional methodology (of using a single radiation detector), boosting the overall performance of the approach. A small robot crawler with LiDAR was first assembled and then modified to install a radiation sensor and thermal imager. The system is controlled and operated wirelessly, displaying real-time radiation/thermal/optical information for the scene under surveillance. In this phase, the system has been successfully assembled/tested and an approach to fuse data from various sensors has been proposed using Python. The presentation covers details of the multimodal system, including challenges encountered in the development, and its testing with radioactive materials. Beyond emergency response, the developed system has direct applications in tasks related to routine radiation monitoring at nuclear facilities, especially areas with high radiation and ambient temperature.