Assessment of damage in exhaust ducts and cavities is necessary to evaluate aircraft readiness and flight safety. Currently, manual inspections are required to visually locate defects in these confined spaces, and log information into an assessment system. These methods for conducting surface inspections of exhaust ducts in manned and unmanned low-observable (LO) aircraft are time consuming and error prone. Furthermore, next-generation Uninhabited Aerial System (UAS) are likely to utilize ducts that are inaccessible to humans. An automated inspection system that can reduce inspection times, minimize human error, and provide access to confined spaces will benefit the Air Force by significantly increasing aircraft reliability and availability, while reducing lifecycle maintenance costs. To address this need, IAI and Boulder Imaging are endeavoring to develop an Autonomous Robotic Inspection System (ARIS) for identifying, mapping, and recording surface defects in exhaust ducts. The key innovation in this program is a self-localizing sensor head, equipped with an imaging solution and corresponding software, that will automatically detect and characterize defects in exhaust duct coatings and register their locations in the aircraft coordinate system. The feasibility of this concept will be demonstrated through the development of a modular sensor head prototype and associated algorithms for localization and defect detection. A trade study will determine the best mobility platform . Then, the hardware and software design will be optimized and the sensor head will be integrated with the chosen mobility platform. This technology can also be useful for the inspection of confined spaces in military aircraft, commercial aircraft, and for other industrial applications.