Overview
This week explored the world of 3D scanning and printing. While 3D printing allows us to create objects that would be impossible with subtractive manufacturing, 3D scanning enables us to digitize the physical world. I experimented with two different scanning approaches: a professional Artec scanner and the AR Code iOS app, each with its own strengths and challenges.
3D Scanning: Two Approaches
The Subject: A Trash Bin
I chose to scan a trash bin from our lab - a seemingly simple object that actually presents interesting challenges for 3D scanning. Its cylindrical shape, reflective surfaces, and varying textures make it a good test case for comparing different scanning technologies. The goal was to create an accurate digital model that could potentially be 3D printed or used in digital environments.
Attempt 1: Artec Professional Scanner
Setting up the Artec professional 3D scanner
The Artec scanner is a professional-grade structured light 3D scanner that promises high accuracy and detailed captures. I was excited to use this sophisticated piece of equipment, but the experience turned out to be more challenging than expected. The scanner works by projecting patterns of light onto the object and capturing the deformation of these patterns to reconstruct the 3D geometry.
However, I encountered several issues during the scanning process. The scanner would occasionally fail to track the object properly, especially when dealing with the reflective metal portions of the trash bin. The software struggled to maintain registration between consecutive frames, causing the scan to "lose" the object. More frustratingly, the machine had a tendency to turn off automatically during longer scanning sessions, interrupting the workflow and forcing me to restart. This instability made it difficult to complete a full, high-quality scan of the trash bin.
While the Artec scanner has the potential to produce highly detailed scans, its sensitivity to lighting conditions, surface properties, and the need for consistent power made it challenging to work with. The learning curve was steep, and the technical issues meant I needed a backup approach.
Attempt 2: AR Code iOS App
Using the AR Code iOS app for photogrammetry-based scanning
The app processing captured images into a 3D model
After the challenges with the Artec scanner, I turned to the AR Code iOS app, which uses photogrammetry to create 3D models. This approach is fundamentally different - instead of structured light, it uses the iPhone's camera and LiDAR sensor combined with computer vision algorithms to reconstruct 3D geometry from multiple photos taken from different angles.
The AR Code app proved to be remarkably stable and user-friendly. The interface guided me through the scanning process, showing which areas needed more coverage and providing real-time feedback on scan quality. I simply walked around the trash bin, capturing it from various angles while the app automatically processed the images. The entire process felt intuitive and responsive, with none of the technical hiccups I experienced with the Artec scanner.
Final 3D model generated by AR Code
Size reference with hand for scale verification
The resulting model was surprisingly accurate, capturing both the overall shape and many surface details of the trash bin. While it may not have the sub-millimeter precision of a professional scanner, the AR Code app delivered a practical, usable 3D model with minimal fuss. The stability and reliability of this consumer-grade solution impressed me - it just worked, consistently and predictably.
3D Model Visualization
Below is the interactive 3D model of the trash bin, scanned using the AR Code app. You can rotate, zoom, and explore the model to see the detail captured by mobile photogrammetry technology.
3D Printing the Scan
The scanned trash bin 3D printed in miniature
To complete the digital-to-physical loop, I 3D printed the scanned model. The print demonstrates the full workflow: physical object → digital scan → 3D print → new physical object. While the printed version is much smaller than the original (limited by printer bed size and time constraints), it captures the essential form and character of the trash bin remarkably well.
The print quality reveals both the strengths and limitations of the scanning process. Fine details like the rim and body contours are well-preserved, though some surface texture is smoothed out during the mesh processing. This exercise highlighted an interesting aspect of digital fabrication: we can now easily replicate objects at different scales, edit them digitally, and produce modified versions - something impossible with traditional manufacturing.
Reflections on Scanning Technologies
Professional vs. Consumer Tools
This project revealed an interesting dynamic in digital fabrication tools. The professional Artec scanner, despite its higher cost and theoretical capabilities, proved less reliable than the consumer-grade iOS app. This doesn't mean professional scanners are inferior - they can achieve higher precision and capture more complex geometries when properly configured and operated by experienced users. However, the gap between professional and consumer tools is narrowing rapidly, especially for common use cases.
The AR Code app's success comes from its integration with the iPhone's sensor suite and clever software design. Apple's LiDAR sensor, combined with sophisticated photogrammetry algorithms, delivers results that are "good enough" for most applications while being dramatically easier to use. The app handles lighting variations, automatically guides coverage, and processes everything on-device without requiring powerful workstation hardware.
Lessons Learned
Working with both scanning systems taught me that success in digital fabrication isn't just about having the most advanced equipment. Reliability, ease of use, and workflow integration matter enormously. The Artec scanner's automatic shutdowns and tracking failures created friction that disrupted the creative process, while the AR Code app's stability allowed me to focus on capturing good data rather than fighting technical issues.
I also learned that object properties significantly affect scanning success. Reflective surfaces, uniform colors, and transparent materials all challenge optical scanning systems. The trash bin's metal components caused issues for both systems, though the photogrammetry approach handled them more gracefully by using multiple views to reconstruct problematic areas.
Finally, this project reinforced that 3D scanning and printing are complementary technologies that enable powerful new workflows. Being able to capture, modify, and reproduce physical objects digitally opens up possibilities for restoration, customization, and documentation that were previously impractical. As both technologies continue improving and becoming more accessible, I expect to see them used in increasingly creative ways.
Technical Details
Artec Scanner Specifications
The Artec scanner uses structured blue light technology with high-resolution cameras to capture 3D geometry and color texture. It's capable of sub-millimeter accuracy but requires stable power, controlled lighting, and careful technique to achieve optimal results.
AR Code App Workflow
The AR Code app leverages the iPhone's LiDAR sensor and camera system to perform real-time photogrammetry. The process involves capturing multiple images from different angles while the app's computer vision algorithms identify common features and reconstruct 3D geometry. The app processes everything locally on the device and exports standard mesh formats compatible with 3D printing software.
3D Printing Parameters
The miniature trash bin was printed using PLA filament on a Bambu Lab P1S printer. The model was scaled down to approximately 1:20 of the original size to fit within print time constraints. Layer height was set to 0.2mm for a balance between detail and speed, with 15% infill for structural stability.