ARIS - Autonomous Robotic Inspection System

ABSTRACT:Current methods for inspecting exhaust ducts in low-observable (LO) aircraft are time consuming and error prone. Furthermore, next-generation aircraft are likely to utilize ducts with confined spaces that are inaccessible to maintainers. Technology that can reduce inspection times, minimize errors and provide access to confined spaces will benefit the Air Force by increasing aircraft availability and reducing lifecycle maintenance costs. To address this need, Intelligent Automation and Boulder Imaging propose to develop ARIS, an Autonomous Robotic Inspection System for identifying and mapping surface defects in exhaust ducts. The key innovation is the integration of a self-localizing robot equipped with an optical imaging sensor and associated control and inspection software. The system provides autonomous control of the robot to enable full coverage of the duct surface. It automatically detects and characterizes defects in coatings and registers their location in the aircraft coordinate system. In Phase I, a sensor head prototype and algorithms for localization and defect detection were developed. In Phase II, a robotic inspection system prototype targeted for a specific LO platform will be designed, built and demonstrated in a representative environment.BENEFIT:The proposed Autonomous Robotic Inspection System will automate the process of exhaust duct defect detection and analysis. It will decrease inspection time, improve accuracy, reduce sources of human error, enable inspection of confined spaces and improve inspection safety. This inspection technology will benefit the Air Force by significantly increasing aircraft availability and reliability while reducing lifecycle maintenance costs. Transition applications include inspection of commercial aircraft engines and other hard-to-access enclosed spaces on both airplanes and ships.