A Robot-Assisted Large-Scale Inspection of Wind Turbine Blades in Manufacturing Using an Autonomous Mobile Manipulator  
[PERSON]  
1 laAM Institute, Faculty of Mechanical Engineering and Mechatronics, University of Applied Sciences Aachen, 52074 Aachen, Germany; [EMAIL_ADDRESS] (P.C. ); [EMAIL_ADDRESS] (H.D. ); [EMAIL_ADDRESS] (S.K.) [PERSON]  
1 laAM Institute, Faculty of Mechanical Engineering and Mechatronics, University of Applied Sciences Aachen, 52074 Aachen, Germany; [EMAIL_ADDRESS] (P.C. ); [EMAIL_ADDRESS] (H.D. ); [EMAIL_ADDRESS] (S.K.) [PERSON]  
1 laAM Institute, Faculty of Mechanical Engineering and Mechatronics, University of Applied Sciences Aachen, 52074 Aachen, Germany; [EMAIL_ADDRESS] (P.C. ); [EMAIL_ADDRESS] (H.D. ); [EMAIL_ADDRESS] (S.K.) [PERSON]  
2 Faculty of Engineering and Built Environment, Tshwane University of Technology, Pretoria 0001, South Africa 2  
be used to generate a detailed layer-by-layer visualization of a rotor blade [9]. Therefore, it is possible to locate imperfections in 3D. However, the underlying algorithms for the 3D reconstruction require a surface orthogonal sensor alignment and a low measurement uncertainty of the sensor pose during the scanning process. These requirements exclude a manual execution with handheld devices. Figure 1 shows a schematic of the manufacturing of a rotor blade, including the two main components: aerosols and shear webs. The typical diameter of a wind turbine rotor, including the blades, has increased from 54 m (2005) to 158 m (2017) for onshore and from 76 m (2005) to 164 m (2015) for offshore installations [11]. The huge dimensions of the rotor blades complicate the inspection processes, which is why they are mostly performed manually by human workers. The automation of the inspection processes has great potential to increase the overall productivity and to create a consistent reliable database for each individual rotor blade. Such an automation approach must be large-scaled and flexible to cover the high variety of rotor blade dimensions. An _autonomous industrial mobile manipulator_ (AIMM) [13] combines the flexibility of an industrial robot arm (manipulator) with the mobility of an autonomous mobile robot (AMR). Equipped with various sensors, AIMMs are capable of autonomous navigation, even in dynamic and large-scale production environments. Furthermore, the perceived data can be used to realize a shared human-robot workspace, which is of particular importance for manual labor-dominated production types. One of the first AIMMs was introduced in 1984: MORO [14]. MORO was capable of navigating on the shopfloor and executing pick and place tasks. Based on this pioneering work, many further developments were carried out, focusing on different industrial applications: part feeding [15; 16; 17], transportation and assembly [18; 19; 20], as well as large-space manufacturing [21; 22; 23]. In recent years, inspection robots have become more present in different domains, such as the oil and gas industry [24; 25], the power industry [26; 27], and civil infrastructure [28]. Therefore, the idea to utilize an AIMM for inspection tasks is obvious. In contrast to recent developments in the area of inspection robots, our approach focuses on the motion planning addressing the surface orthogonal sensor alignment and the special requirements of a shared human-robot workspace in an industrial context. Therefore, we make use of the AIMM OMNIVIL [29]. OMNIVIL consists of a self-built mobile platform. The mobile platform was designed to address the needs in a dynamic production environment, such as positioning, accuracy, and maneuverability. Therefore, the platform is based on four Mecanum wheels [30], whereby a pivoting axle guarantees continuous ground contact. The collaborative manipulator UR5 is mounted on top of the mobile platform. The sensor concept includes various sensor types to perceive the environment and the internal state of the robot.