Author(s): Trevor Carter
Mentor(s): Larry Howell, Jake Sutton
Institution BYU
This work introduces a novel method that analyzes the relative alignment of panels in origami-inspired deployable systems. It is motivated by the need to create deployable systems that are accurate enough for use in future space telescopes, especially where optical and radio instruments require repeatable deployment. Knowing the post-deployment position of panels is important for evaluating the accuracy and precision of panel alignment. Motion-capture camera systems have been described in existing literature, however, they involve bespoke setups and focus on the deployment process rather than the precision of the deployed-state alignment. The proposed method processes data from 3D scans of the panels after several deployment cycles and evaluates panel alignment while minimizing manual processing. A high-fidelity 3D scanner is employed, such as a laser line probe system. The deployable system is actuated into its final state, scanned, then stowed and deployed again. This process is repeated until sufficiently many samples are obtained. For each of the samples, small selections of points are made on each panel surface with a paintbrush tool. For a single sample, the user assigns descriptive labels to each of the panels. A robust algorithm re-orients all remaining scans to align with the labeled sample, propagating the labels automatically. The positions and orientations of all panels for each scan instance are calculated and stored in a specified file format. Optionally, a ground panel may be selected to act as the origin for all calculations. Maximal, minimal, and average misalignments, as well as regions of low precision or accuracy, are computed, saved, and visualized. This process is demonstrated with thickness accommodated patterns, namely the degree-four vertex, flasher, and Miura-ori. A precisely machined metal surface serves as a reference standard to calibrate measurement confidence and quantify error tolerances in detecting panel deviations. The functioning Python code and user interface are expected to be made publicly available.