Visual-based pose determination of uncontrolled space targets using retroreflective markers for debris removal operations

The need to remove space junk from crowded orbital regimes has fostered the interest towards the development of technologies enabling autonomous active debris removal missions. Due to the lack of a dedicated inter-satellite link, approach and docking/berthing operations must rely on visual-based solutions to ensure accurate relative navigation capabilities. In this respect, while the current debris population is composed of uncooperative targets, future satellites are expected to be equipped with fiducial markers to ease the relative navigation function of an autonomous chaser if a servicing/removal mission is requested. These markers shall be placed on all the available target faces e to ensure the capability to handle also tumbling satellites. In this framework, this work deals with the design and testing of a relative navigation module for proximity operations towards passively cooperative space targets. The module features a monocular camera and an active, low-power, wide-beam laser, both operating in the infrared band. This emitter is used to illuminate markers made of highly reflective material, having various geometries on different faces of the target so that markers’ identification is performed exploiting the knowledge of their shape. The adopted solution allows distinguishing the faces of the target during the approach even when no apriori information is available (pose acquisition). First, numerical tests are executed in a dedicated simulation environment including a synthetic image generator (based on the open-source software Blender. A large variability of pose conditions is reproduced including variable distances from the target and increasing observation angles. Then, a campaign of experimental tests is carried out employing a prototype of the relative navigation module made with commercial-off-the-shelf components. Numerical results demonstrate that the module can detect and discriminate 6-cm size markers with various shape from 15 m distance up to docking/berthing, while experimental tests, performed up to distances of 8 m, confirm the capability to detect the shape of even smaller markers. The algorithm proves to be also robust to large observation angles, both in numerical and experimental validations, showing mm-level detection errors. The analysis is finally complemented by an evaluation of the execution time.