EX-SCAN: Autonomous Inspection System for Aircraft Surface Coatings

ABSTRACT: Current methods for inspecting the external surface of manned and unmanned low-observable (LO) aircraft are time consuming and error prone. Technology that can reduce inspection times and minimize human error will benefit the Air Force by significantly increasing aircraft reliability and availability while reducing lifecycle maintenance costs. To address this need, Intelligent Automation and The Robotics Institute at Carnegie Mellon University propose to develop EX-SCAN, an autonomous non-contact inspection system that can detect, register and characterize defects in aircraft external surface coatings. The key innovation is a self-localizing sensor array equipped with an imaging solution and corresponding software that will automatically detect and characterize defects in surface 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 prototype system capable of registering and characterizing sample defects. Phase II will optimize the system hardware and software and test EX-SCAN on representative aircraft. BENEFIT: EX-SCAN will automate the process of detecting, registering and characterizing defects in aircraft external surface coatings. It will 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.