## 1 Introduction
### Automated Inspection and Robotic Systems  
In recent years, industrial and academic researchers have contributed to advancing the next generation of aircraft inspection by proposing automated or semi-automated approaches that utilise various technologies such as vortex robots, unmanned aerial vehicles (UAVs), wheeled mobile robots, and robotic arms. A notable example of a mobile platform is the Air-Cobot wheeled mobile robot, developed by [PERSON] et al. [19] in 2017. This system developed a 3D point cloud inspection system capable of detecting and characterising defects on the fuselage of a real Airbus A320 aeroplane. The data were collected with the Artec Eva 3D scanner mounted on the Air-Cobot wheeled mobile robot. Particular attention should be given to the Air-Cobot wheeled mobile robot, which stands out due to its unique combination of Non-Destructive Testing (NDT), Autonomous Navigation, and Human-Robot Interaction (HRI) capabilities. The robot was equipped with a 3D scanner and a PTZ camera for NDT purposes. It could safely navigate autonomously around aircraft, avoiding obstacles. Additionally, the robot was adaptive, meaning it could learn from human interactions and improve its efficiency over time [27; 28; 29; 30; 31]. As previously mentioned, the inspection process was fully automated, following a pre-defined trajectory to detect defects such as dents and scratches. Novel techniques were also employed to accurately measure the defects' size, depth and orientation. The system's performance was compared against ground truth measurements using high-precision measuring equipment [19]. Expanding on robotised inspection platforms, [PERSON] et al. [32] developed a prototype vortex adhesion-based robotic system for automated aircraft inspections in real-world environments. Unlike wheeled mobile robots operating on flat surfaces, this solution could move across curved and inclined aircraft structures, such as fuselages and wings. The robot was built for hangar and field conditions, addressing challenges like surface accessibility and environmental variability. Its integration of an eddy current testing (ECT) probe allowed it to detect cracks and corrosion in metallic aircraft components. A key advantage of this system was its modular design. Through laboratory and field testing, the system proved capable of accurately identifying defects, demonstrating the potential of robotic automation in aircraft maintenance. Another robotized system was introduced by [PERSON] et al. [20], who proposed a 3D scanning system capable of detecting surface damages during semi-automated aircraft inspections. Specifically, this technology could inspect in-service honeycomb sandwich panels and accurately detect and characterise dents. This promising approach could estimate dent depth with a false error rate within 0.04 \(\pm\) 0.06 mm. The preferred point cloud acquisition system was the FARO(r) (Lake Mary, FL, USA) Edge 3D scanning system, consisting of a FARO Laser Line Probe and SmartArm (Toronto, ON, Canada) technology. [PERSON] et al. [21] adopted a slightly different approach, utilising a \"vortex\" wall-climbing robot integrated with a heat pump as a stimulation source and an infrared sensor for real-time temperature acquisition. This setup was used to inspect aircraft honeycomb composite structures and detect the presence of water. The inspection was conducted remotely via Bluetooth, and the processed thermal images were validated against those captured by a Fluke thermal camera. The study concluded that the method was sufficiently reliable for detecting water ingress. Unmanned aerial vehicles (UAVs) are increasingly being recognised for their potential to automate and enhance the process of visual aircraft inspection. In the late 2010s, companies like Blue Bear and Createc, with their RISER project, along with Airbus and its Aircam programme, started focusing on developing automated UAV systems for aircraft inspections [33].