Uncrewed aerial systems (UAS) have steadily become more prevalent in both defense and industrial applications. Nuclear detection and deterrence is one such field that has given rise to many new opportunities for UAS operations. There is a need to research and develop methods to integrate existing radiation detection technology with UAS capable of flying low-altitude missions. This low-altitude scanning can be achieved by combining small and lightweight radiation detectors and state-of-the-art aircraft and avionics. High resolution mapping can then be conducted using the results of these scans. Significant work has been conducted in this field by both private industry and academic institutions, including the Uncrewed Systems Lab (USL) at Virginia Tech. This work seeks to expand this body of knowledge and provide practical experimental information to showcase and validate the efficacy of radiation detection via UAS. Multiple missions were conducted using samples of 137Cs and 60Co as a radioactive source. Various filtering methods were applied to the results of these missions to produce visual maps that aid in the localization of an unknown source to compare various flight parameters. In addition, significant work was conducted to characterize two radiation detectors available to the USL to provide metrics to assist in the UAS design and flight planning. Finally, the detectors were taken to Savannah River National Laboratories to conduct experiments to provide information to aid future designs and missions that wish to detect a wider variety of radioactive sources. / Master of Science / Drones are becoming more common in many applications for both industry and defense. One of these applications is in the field of nuclear detection which seeks to both regulate the shipping of radioactive material as well as aid response to nuclear disasters. Methods need to be researched to combine existing radiation detectors with new drone technology. These new state-of-the-art drones are capable of flying at very low altitudes which can allow for the use of small and lightweight radiation detectors. Past work in this area, including at the Uncrewed Systems Lab (USL) at Virginia Tech, has explored larger scale aircraft as well as simulated radioactive sources. This work expands the existing knowledge of this field by providing scan results from real radioactive sources and drone flights. Multiple search flights were conducted using small quantities of radioactive cesium and cobalt. Maps were then produced using the information from these flights to showcase the system's ability to quickly locate the areas of high radioactivity. Flights were flown with different altitudes and speeds to determine the effects on mapping accuracy. Finally, experiments were conducted at Savannah River National Laboratories on a variety of more controlled nuclear materials to help inform future drone designs and mission planning.

Autonomous vehicle navigation is a complex and challenging task. Land and aerial vehicles often use highly accurate GPS sensors to localize themselves in their environments. These sensors are ineffective in underwater environments due to signal attenuation. Autonomous underwater vehicles utilize one or more of the following approaches for successful localization and navigation: inertial/dead-reckoning, acoustic signals, and geophysical data. This thesis examines autonomous localization in a simulated environment for an OpenROV Underwater Drone using a Kalman Filter. This filter performs state estimation for a dead reckoning system exhibiting an additive error in location measurements. We evaluate the accuracy of this Kalman Filter by analyzing the effect each parameter has on accuracy, then choosing the best combination of parameter values to assess the overall accuracy of the Kalman Filter. We find that the two parameters with the greatest effects on the system are the constant acceleration and the measurement uncertainty of the system. We find the filter employing the best combination of parameters can greatly reduce measurement error and improve accuracy under typical operating conditions.