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A Flexible Image Processing Framework for Vision-based Navigation Using Monocular Image Sensors

Tzschichholz, Tristan and Boge, Toralf and Benninghoff, Heike (2011) A Flexible Image Processing Framework for Vision-based Navigation Using Monocular Image Sensors. 8th International ESA Conference on Guidance, Navigation & Control Systems, 05.-10. Jun. 2010, Karlsbad, Tschechien.

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Abstract

On-Orbit Servicing (OOS) encompasses all operations related to servicing satellites and performing other work on-orbit, such as reduction of space debris. Servicing satellites includes repairs, refueling, attitude control and other tasks, which may be needed to put a failed satellite back into working condition. A servicing satellite requires accurate position and orientation (pose) information about the target spacecraft. A large quantity of different sensor families is available to accommodate this need. However, when it comes to minimizing mass, space and power required for a sensor system, mostly monocular imaging sensors perform very well. A disadvantage is- when comparing to LIDAR sensors- that costly computations are needed to process the data of the sensor. The method presented in this paper is addressing these problems by aiming to implement three different design principles; First: keep the computational burden as low as possible. Second: utilize different algorithms and choose among them, depending on the situation, to retrieve the most stable results. Third: Stay modular and flexible. The software is designed primarily for utilization in On-Orbit Servicing tasks, where- for example- a servicer spacecraft approaches an uncooperative client spacecraft, which can not aid in the process in any way as it is assumed to be completely passive. Image processing is used for navigating to the client spacecraft. In this specific scenario, it is vital to obtain accurate distance and bearing information until, in the last few meters, all six degrees of freedom are needed to be known. The smaller the distance between the spacecraft, the more accurate pose estimates are required. The algorithms used here are tested and optimized on a sophisticated Rendezvous and Docking Simulation facility (European Proximity Operations Simulator- EPOS 2.0) in its second-generation form located at the German Space Operations Center (GSOC) in Weßling, Germany. This particular simulation environment is real-time capable and provides an interface to test sensor system hardware in closed loop configuration. The results from these tests are summarized in the paper as well. Finally, an outlook on future work is given, with the intention of providing some long-term goals as the paper is presenting a snapshot of ongoing, by far not yet completed work. Moreover, it serves as an overview of additions which can improve the presented method further.

Item URL in elib:https://elib.dlr.de/74407/
Document Type:Conference or Workshop Item (Speech, Paper)
Title:A Flexible Image Processing Framework for Vision-based Navigation Using Monocular Image Sensors
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Tzschichholz, TristanDLRUNSPECIFIED
Boge, ToralfDLRUNSPECIFIED
Benninghoff, HeikeDLRUNSPECIFIED
Date:2011
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:rendezvous, docking, simulation, hardware in the loop, vision based navigation, pose estimation
Event Title:8th International ESA Conference on Guidance, Navigation & Control Systems
Event Location:Karlsbad, Tschechien
Event Type:international Conference
Event Dates:05.-10. Jun. 2010
Organizer:ESA
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben On-Orbit Servicing - GNC und VR
Location: Oberpfaffenhofen
Institutes and Institutions:Space Operations and Astronaut Training > GSOC-German Space Operations Center
Deposited By: Boge, Toralf
Deposited On:23 Jan 2012 17:35
Last Modified:31 Jul 2019 19:35

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