# Physical Adaptation of Articulated Robotic Arm into 3D Scanning System
## 3 Results  
### Photogrammetric 3D Digitization  
The 3D digitization process begins with setting up the photo capture equipment and the scene environment. The physical objects used in this process, the Mitsubishi robotic arm, model RV-3 SDB-S15 (Mitsubishi Electric, Tokyo, Japan) [47], and the EinScan Pro 2X (Shining 3D, Hangzhou, China) [48] optical 3D scanner, are shown in Figure 3a and Figure 3b, respectively. For photo capturing, a Canon EOS 1200D camera with an APS-C 18-megapixel CMOS sensor and EF-S 18-55 mm f/3.5-5.6 IS II lens was used. There are no limitations in using this camera and the specified lens. The main influence on the photogrammetric accuracy is the image quality, which depends mostly on lighting conditions, image resolution (sensor size), and lens type (fisheye, normal, wide, etc.). The camera was mounted on a tripod and moved around the robotic arm in five concentric rings, moving from bottom to top, and around the 3D scanner in two rings. The increment angle from shot to shot was approximately 10 to 15 degrees. A total of 169 high-resolution photographs (5184 \(\times\) 3456 px) were captured. The 3D scanner was photographed on a rotary table, where 37 photos were captured, but only one half of the 3D scanner was sufficient for the reconstruction. By using the tripod, potential shake and blur effects were eliminated. The scale of the objects was determined by placing coded markers around the object and placing them on a turntable, with a known and defined distance between them. The coded markers were generated by photogrammetric software and printed on standard A4 white paper. These markers can be automatically detected by photogrammetric software in the image processing stage. Scale validation was conducted by measuring easily accessible features using a caliper with an accuracy of 0.05 mm and comparing with measurements on 3D models. Figure 2: Workflow diagram of the development of a fully useable 3D-printed connection element. The lighting conditions were carefully optimized for the photographic camera settings, such as aperture (f11), shutter speed (3/5 s), and ISO (200), which provide the appropriate depth of field, ensuring high-quality images for 3D digitization. After the photos were successfully acquired, they were processed using Reality Capture v1.5 (Epic Games, Cary, NC, USA) photogrammetric software, and a mesh 3D model was generated. With Reality Capture, it is possible to obtain accurate 3D models, even those with sub-millimeter resolution [49]. The resolution of the 3D model depends on the quality and resolution of the images and the distance of the capturing camera from the object. The basic workflow for photogrammetry reconstruction was used, and it included importing images into software, aligning images, creating a sparse point cloud, mesh reconstruction, and texture application. Figure 4a,b show the 3D models with the texture and camera locations obtained by photogrammetric reconstruction. An automated marker detection option for marker detection was used, which was based on the markers with which the scale was defined. Photogrammetric 3D models usually require additional post-processing because of the presence of noise and extra geometry generated from the environment. Post-processing involves several key steps, including noise removal, polygon reduction, hole filling, and geometry repair. For noise removal, a smoothing method was used, and the threshold value was set to 0.1 mm, which  
Figure 4: Photogrammetric 3D digitization: (**a**) Mitsubishi articulated robotic arm; (**b**) Shining 3D EinScan Pro 2X Optical 3D scanner. Figure 3: Physical components for 3D digitization: (**a**) Mitsubishi articulated robotic arm, model RV-3 SDB-S15; (**b**) Shining 3D EinScan Pro 2X optical 3D scanner. eliminated most of the noise. The purpose of polygon reduction is to reduce the number of sufficient polygons to maintain accuracy. The smaller holes were filled with an automated tool, while the larger holes were filled manually.