Containers for storage of Special Nuclear Material (SNM) have to be robust and long-lasting. While a variety of purpose-specific containers have been developed and generally show outstanding performance, container health must nonetheless be monitored with some frequency. However, due to large quantities of stored material and exposure to radiation it is not feasible to perform in-depth container surveillance on many containers. Container problems are often discovered only once exposure risk reaches a significant level. Robotic automation technology can be leveraged to supplement current surveillance methods, improve data collection, and reduce the delay for container issue identification and remediation. Los Alamos National Laboratory (LANL) conducted a pilot demonstration using a a Waypoint Robotics Vector mobile platform integrated with a Universal Robotics UR5e arm and visual, thermal, and radiological imaging. The system was deployed in a radiological facility where samples of containers and sealed sources, analogous to that expected onsite, were surveyed for container health while neutron radiation rates were mapped in the test area. Performance was evaluated based on the successful identification of damaged containers and those containing SNM.
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