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