Matlab Machine Learning Directed Study: Report 2 Anson’s Projects focuses on a machine learning directed study where 3D models of satellite assemblies are utilized to simulate debris data. The models, sourced from GrabCAD, were processed using Blender to create 108 unique parts. An algorithm implemented in Julia calculates essential properties like moments of inertia and volume,
Matlab Machine Learning Directed Study: Report 1 Anson's report details a machine learning directed study focused on analyzing 3D models of a CubeSat designed to detect orbital debris. Initially, the author gathered high-quality models from GrabCad to simulate data collection, specifically selecting a 6U CubeSat model consisting of 48 unique parts. Data preparation involved extracting
Orbital Debris Space Debris Characterization Using Machine Learning Methods The project focuses on characterizing space debris using advanced machine learning methods and 3D scanning techniques. Currently, NASA tracks over 23,000 debris objects, and the increasing number of satellites in Low Earth Orbit raises collision risks, potentially leading to a dangerous cascade of debris. The proposal aims to enhance
