- Treffer 1 von 1
Lidar pose tracking of a tumbling spacecraft using the smoothed normal distribution transform
Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-313738
- Lidar sensors enable precise pose estimation of an uncooperative spacecraft in close range. In this context, the iterative closest point (ICP) is usually employed as a tracking method. However, when the size of the point clouds increases, the required computation time of the ICP can become a limiting factor. The normal distribution transform (NDT) is an alternative algorithm which can be more efficient than the ICP, but suffers from robustness issues. In addition, lidar sensors are also subject to motion blur effects when tracking a spacecraftLidar sensors enable precise pose estimation of an uncooperative spacecraft in close range. In this context, the iterative closest point (ICP) is usually employed as a tracking method. However, when the size of the point clouds increases, the required computation time of the ICP can become a limiting factor. The normal distribution transform (NDT) is an alternative algorithm which can be more efficient than the ICP, but suffers from robustness issues. In addition, lidar sensors are also subject to motion blur effects when tracking a spacecraft tumbling with a high angular velocity, leading to a loss of precision in the relative pose estimation. This work introduces a smoothed formulation of the NDT to improve the algorithm’s robustness while maintaining its efficiency. Additionally, two strategies are investigated to mitigate the effects of motion blur. The first consists in un-distorting the point cloud, while the second is a continuous-time formulation of the NDT. Hardware-in-the-loop tests at the European Proximity Operations Simulator demonstrate the capability of the proposed methods to precisely track an uncooperative spacecraft under realistic conditions within tens of milliseconds, even when the spacecraft tumbles with a significant angular rate.…
Autor(en): | Léo Renaut, Heike Frei, Andreas Nüchter |
---|---|
URN: | urn:nbn:de:bvb:20-opus-313738 |
Dokumentart: | Artikel / Aufsatz in einer Zeitschrift |
Institute der Universität: | Fakultät für Mathematik und Informatik / Institut für Informatik |
Sprache der Veröffentlichung: | Englisch |
Titel des übergeordneten Werkes / der Zeitschrift (Englisch): | Remote Sensing |
ISSN: | 2072-4292 |
Erscheinungsjahr: | 2023 |
Band / Jahrgang: | 15 |
Heft / Ausgabe: | 9 |
Aufsatznummer: | 2286 |
Originalveröffentlichung / Quelle: | Remote Sensing (2023) 15:9, 2286. https://doi.org/10.3390/rs15092286 |
DOI: | https://doi.org/10.3390/rs15092286 |
Allgemeine fachliche Zuordnung (DDC-Klassifikation): | 5 Naturwissenschaften und Mathematik / 52 Astronomie / 520 Astronomie und zugeordnete Wissenschaften |
Freie Schlagwort(e): | lidar; normal distribution transform; pose tracking; uncooperative space rendezvous |
Datum der Freischaltung: | 07.02.2024 |
Datum der Erstveröffentlichung: | 26.04.2023 |
Lizenz (Deutsch): | CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International |