Real-Time Image-Based Relative Pose Estimation and Filtering for Spacecraft Applications
| Autor: | Siddarth Kaki, Jacob Deutsch, Kevin Black, Asher Cura-Portillo, Brandon A. Jones, Maruthi R. Akella |
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| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Journal of Aerospace Information Systems. :1-19 |
| ISSN: | 2327-3097 1940-3151 |
| DOI: | 10.2514/1.i011196 |
| Popis: | The problem of estimating relative pose for uncooperative space objects has garnered great interest, especially within applications such as on-orbit assembly and satellite servicing. This paper presents a full end-to-end open-source pose estimation and filtering pipeline using monocular camera images for space systems applications. The algorithm pipeline consists of three main components: 1) a set of neural networks to perform keypoint regression; 2) a pose estimation component, implementing both nonlinear least-squares and perspective-[Formula: see text]-point solvers; and 3) a full-pose tracking component, implementing a multiplicative extended Kalman filter. While this software pipeline is designed to be a general-purpose solution, its development was motivated and driven by the size, weight, power, and cost requirements of the NASA Seeker CubeSat program. A combination of real and simulated results is presented to evaluate the neural network components, and simulated time-series results are presented to evaluate the performance of the full pipeline on flightlike hardware in real time. |
| Databáze: | OpenAIRE |
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