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| Hauptverfasser: | , , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2509.07932 |
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| _version_ | 1866914030333984768 |
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| author | Gopu, Bala Prenith Reddy Huber, Timothy Jacob Nehma, George M. Quinn, Patrick Tiwari, Madhur Ueckermann, Matt Hinckley, David McKenna, Christopher |
| author_facet | Gopu, Bala Prenith Reddy Huber, Timothy Jacob Nehma, George M. Quinn, Patrick Tiwari, Madhur Ueckermann, Matt Hinckley, David McKenna, Christopher |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_07932 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Dynamic Scene 3D Reconstruction of an Uncooperative Resident Space Object Gopu, Bala Prenith Reddy Huber, Timothy Jacob Nehma, George M. Quinn, Patrick Tiwari, Madhur Ueckermann, Matt Hinckley, David McKenna, Christopher Computer Vision and Pattern Recognition 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. |
| title | Dynamic Scene 3D Reconstruction of an Uncooperative Resident Space Object |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2509.07932 |