ARIS - Autonomous Robotic Inspection System

ABSTRACT: Current 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 UAS are likely to utilize ducts with confined spaces that are inaccessible by human maintainers. Technology 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, Intelligent Automation and Boulder Imaging propose to develop an Autonomous Robotic Inspection System for identifying, mapping and recording surface defects in exhaust ducts. The key innovation 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 location in the aircraft coordinate system. In Phase I, feasibility of the 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. Phase II will optimize the hardware and software design and integrate the sensor head with the chosen mobility platform BENEFIT: The proposed Autonomous Robotic Inspection System will automate the process of exhaust duct defect detection and analysis. It will enable inspection of confined spaces, improve inspection safety, decrease inspection time, improve accuracy and eliminate sources of human error. This inspection technology will benefit the Air Force by significantly increasing aircraft reliability and availability while reducing lifecycle maintenance costs.