6D Pose Estimation and Calibration for Autonomous On-Orbit Servicing using the OOS-SIM

Reliable six-degree-of-freedom pose estimation is a key requirement for autonomous on-orbit servicing (OOS), in which a robotic spacecraft performs tasks such as inspection, maintenance, and life extension of other satellites in orbit. However, generating trustworthy ground truth for algorithm development remains challenging. This thesis investigates calibration, sensor evaluation, and sensor fusion for the OOS-SIM testbed at the German Aerospace Center, which combines industrial robots, a VICON motion capture system, and forward kinematics (FK) to emulate servicer–client satellite interactions. The thesis first formulates the system calibration as an AX = YB hand–eye problem and employs a linear solver to align VICON and FK measurements in a common world frame, achieving sub-millimetre and sub-tenth-degree calibration residuals. A camera-based ground truth concept was then explored using a calibration board observed by an end-effector stereo camera. In practice, exposure limitations, motion blur, and likely changes in camera intrinsics prevented the camera system from providing a reliable reference, and its measurements could not be trusted to outperform VICON or FK. Finally, an Invariant Extended Kalman Filter was implemented to fuse VICON and FK poses on SE(3). The filter exhibited stable and interpretable behaviour, correctly reflecting the chosen sensor covariances, but its benefits were constrained by the lack of a motion model and the absence of dependable ground truth under challenging conditions. Overall, the thesis highlights the critical role of data integrity, calibration design, and experimental setup in establishing meaningful pose ground truth for space robotics research.