Automated 3D data fusion surveys on Spot robot for next generation plant monitoring

Currently, the process of conducting frequent radiation surveys of large and complex areas, such as nuclear power plants, shipping ports, and urban areas, is a labor intensive process that puts personnel at risk of being exposed to unnecessary dose. Collecting and correlating large amounts of radiation data, situational awareness or environmental data from multiple sensors ranging from visual cameras, LiDAR, GPS, and more, is also a labor intensive process that is error prone. Currently deployed robotic systems with multi-sensor payloads collect data independently and require the end user to manually analyze the data. Advanced software and hardware tools are required to enable more intelligent integration of sensors with robotic platforms and automate the correlation, analysis, and fusion of these different types of data to quickly provide actionable information for applications ranging from civil nuclear power to emergency response. This SBIR effort will focus on the development of an intelligent robotic sensor integration package for autonomous data collection, mapping, and investigation of radiological anomalies, as well as a complementary capability to identify changes in radioisotope and dose rate data over time and space to provide actionable insights to end users. In Phase I, initial autonomous data collection and sensor-robot integration and the initial ability to compare and visualize changes in radiological changes of the same area using data sets taken over a set time period were successfully demonstrated. A 3D radiation mapping system was integrated with a quadruped robot and autonomously collected multiple data sets of a source in a shipping container. For the change detection analysis development, visualization and identification of changes between different data sets was demonstrated starting with a simple use case using point sources. Initial change detection analysis was also conducted on more complex source term data sets using real data from a nuclear power plant. In Phase II, continued development towards a commercially viable system for autonomous data collection and automated change detection and trend analysis will be conducted. The end result of this effort is an autonomous and intelligent data collection and analysis capability that will enable safer, more efficient, and more economical operation of the existing U.S. nuclear fleet and the next generation of advanced nuclear reactors. There are significant commercial opportunities to implement the proposed capabilities across the U.S. nuclear fleet to automate plant monitoring, radiation protection, and operational work processes that will benefit currently operating nuclear power plants, as well as advanced next generation reactors currently under development. The results of this SBIR will support both the National Reactor Innovation Center’s efforts to develop complementary innovations that will support sustainability of new advanced nuclear reactor technologies, including advanced robotics with multisensor systems, as well as the DOE’s Light Water Reactor Sustainability Program efforts to replace labor-intensive operations with safer, automated data collection and analysis tools under the Plant Monitoring and Work Process Automation focus area. These capabilities will also enable safer, faster, and more efficient radiation detection, assessment, and response for other applications, including decommissioning, emergency response, homeland security, defense, and international safeguards.