This paper presents a pose estimation routine for tracking attitude and position of an uncooperative tumbling spacecraft during close range rendezvous. The key innovation is the usage of a Photonic Mixer Device (PMD) sensor for the first time during space proximity for tracking the pose of the uncooperative target. This sensor requires lower power consumption and higher resolution if compared with existing flash Light Identification Detection and Ranging (LiDAR) sensors. In addition, the PMD sensor provides two different measurements at the same time: depth information (point cloud) and amplitude of the reflected signal, which generates a grayscale image. In this paper, a hybrid model-based navigation technique that employs both measurements is proposed. The principal pose estimation technique is the iterative closed point algorithm with reverse calibration, which relies on the depth image. The second technique is an image processing pipeline that generates a set of 2D-to-3D feature correspondences between amplitude image and spacecraft model followed by the Efficient Perspective-n-Points (EPnP) algorithm for pose estimation. In this way, we gain a redundant estimation of the target's current state in real-time without hardware redundancy. The proposed navigation methodology is tested in the German Aerospace Center (DLR)'s European Proximity Operations Simulator. The hybrid navigation technique shows the capability to ensure robust pose estimation of an uncooperative tumbling target under severe illumination conditions. In fact, the EPnP-based technique allows to overcome the limitations of the primary technique when harsh illumination conditions arise.
This paper addresses the validation of a robust vision-based pose estimation technique using a Photonic Mixer Device (PMD) sensor as a single visual sensor in the close-range phase of spacecraft rendezvous. First, it was necessary to integrate the developed hybrid navigation technique for the PMD sensor into the hardware-in-the-loop (HIL) rendezvous system developed by the German Aerospace Center (DLR). Thereafter, HIL tests were conducted using the European Proximity Operation Simulator (EPOS) with sun simulation and in total darkness. For the future missions with an active sensor, e.g., a PMD camera, it could be useful to use only its own illumination during the rendezvous phase in penumbra or umbra, instead of additional flash light. In some tests, the rotational rate of the target object was also tuned. Unlike the rendezvous tests in other works, here we present for the first time closed-loop approaches with only depth and amplitude images of a PMD sensor. For the rendezvous tests in the EPOS laboratory, the Argos3D camera was used at the range of 8 to 5.5 meters; the performance showed promising results.
The problem described in this paper concerns the problem of initial pose estimation of a non-cooperative target for space applications. We propose to use a Photonic Mixer Device (PMD) sensor in a close range for the visual navigation in order to estimate position and attitude of the space object. The advantage of the ranging PMD sensor is that it provides two different sources of data: depth and amplitude information of the imaging scene. In this work we make use of it and propose a follow-up initial pose improvement technique with the amplitude images from PMD sensor. It means that we primary calculate the pose of the target with the depth image and then correct the pose to get more accurate result. The algorithm is tested for the set of images in the range 8 to 4.9 meters. The obtained results have shown the evident improvement of the initial pose after correction with the proposed technique.
The problem described in this paper concerns the problem of initial pose estimation of a non-cooperative target for space applications. We propose to use a Photonic Mixer Device (PMD) sensor in a close range for the visual navigation in order to estimate position and attitude of the space object. The advantage of the ranging PMD sensor is that it provides two different sources of data: depth and amplitude information of the imaging scene. In this work we make use of it and propose a follow-up initial pose improvement technique with the amplitude images from PMD sensor. It means that we primary calculate the pose of the target with the depth image and then correct the pose to get more accurate result. The algorithm is tested for the set of images in the range 8 to 4.9 meters. The obtained results have shown the evident improvement of the initial pose after correction with the proposed technique.
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