Tracking Additive Manufacturing Using Machine Vision
Abstract
This project investigates multiple methods of verifying Additive Manufacturing (AM) products using computer vision, including feature-based visual odometry and image registration. With the rise of AM comes cyber-physical risks and the potential for part defects. Feature-based Visual Odometry (VO) is a field of computer vision research that uses information from images to calculate the relative motion of the camera through space. We developed a VO algorithm to reconstruct extruder position and motion from stereo images as a cost-effective means to monitor AM part construction. Preliminary results in simulation demonstrate feasibility of the proposed VO method and identify factors that may limit performance. In addition to VO, we seek to verify product quality using image registration and template matching techniques. Investigation with feature-based methods led to the development of a print bed tracking pattern, which enables the estimation of the extruders position and orientation. Combined with knowledge of the product's pose and the position of the camera module a render of the product can be created. This simulated image can be compared to images captured from the camera module using image registration algorithms to check for defects. Preliminary results yield successful image segmentation and detection of structural defects.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 12, 2021
- Accession Number
- AD1149666
Entities
People
- Lenning A. Iv Davis
Organizations
- United States Naval Academy