Development of mobile platform for inventory and inspection applications in nuclear environments

Worker radiation exposure is a major constraint in nuclear facilities, but advances in robotics have the potential to produce novel solutions to this problem beyond the traditional methods of the nuclear field. This dissertation details recent work towards this goal within the Nuclear and Applied Robotics Group of The University of Texas at Austin. The primary contributions relate to autonomous, mobile radiation surveying and statistical analysis of acquired data to reach quantitative conclusions about radioactive sources in the survey environment. This work has produced a mobile robotic platform capable of performing an autonomous radiation survey routine over a commanded area of a nuclear facility. If signs of anomalous radiation sources are detected in the area, the system possesses features to locate and characterize them. This procedure utilizes a method of statistically analyzing the data using Recursive Bayesian Estimation. This process is supported by isotopic identification via gamma spectroscopy, which enables efficiency improvements to the method. The developed implementation makes significant improvements to prior literature in locating radiation sources. The practical result is that radiation fields can be characterized with fewer total measurements and with greater mathematical robustness, all without human presence in the radiation area.Mechanical Engineerin