Dynamic Scene 3D Reconstruction of an Uncooperative Resident Space Object
It addresses the problem of characterizing uncooperative space objects for on-orbit servicing and debris removal missions, but is incremental as it focuses on evaluating existing methods.
This study evaluated existing 3D reconstruction algorithms for dynamic scenes to reconstruct tumbling uncooperative space objects, finding that Neuralangelo on static scenes produced 3D meshes closely matching CAD models with minimal errors and artifacts.
Characterization of uncooperative Resident Space Objects (RSO) play a crucial role in On-Orbit Servicing (OOS) and Active Debris Removal (ADR) missions to assess the geometry and motion properties. To address the challenges of reconstructing tumbling uncooperative targets, this study evaluates the performance of existing state-of-the-art 3D reconstruction algorithms for dynamic scenes, focusing on their ability to generate geometrically accurate models with high-fidelity. To support our evaluation, we developed a simulation environment using Isaac Sim to generate physics-accurate 2D image sequences of tumbling satellite under realistic orbital lighting conditions. Our preliminary results on static scenes using Neuralangelo demonstrate promising reconstruction quality. The generated 3D meshes closely match the original CAD models with minimal errors and artifacts when compared using Cloud Compare (CC). The reconstructed models were able to capture critical fine details for mission planning. This provides a baseline for our ongoing evaluation of dynamic scene reconstruction.