An intelligent hexapod robot for inspection of airframe components oriented by deep learning technique

The global competition in the manufacturing industry is becoming more and more aggressive each day. The technologies of Industry 4.0, based on the Internet of Things (IoT), have been pursued in Research and Development, manufacturing, and management processes. In this way, the research consolidated in this paper aims to extend the use of nature-inspired robots in aircraft manufacturing, exploiting the state-of-art technologies and their benefits for productive purposes. This research presents an integrated robotic solution for the inspection of fastened structural joints by a hexapod crawler robot, equipped with a vision sensor, embedded systems, managed by a deep learning algorithm and coordinated in the cloud that moves on the surface of an aircraft providing real-time monitoring via mobile devices. A case study regarding the inspection of airframe fasteners was carried out to demonstrate the application of the proposed solution, the developed method, and its tasks. The automation of the inspection process strives to increase efficiency, cost reduction, streamline ergonomics issues, and support aircraft fabricators. This novel proposal looks for an innovative application in the aeronautical sector based on state-of-art technology faced by intelligent manufacturing.