A review of state-of-the-art 6D pose estimation and its applications in space operations

Increase in autonomous systems now requires for these systems to work in close proximity of other objects in their environments, with many tasks that need to be done on environment objects for eg., assembly, transportation, rendezvous, docking, or to avoid them like collision detections/avoidance, path planning etc. In this literature review we discuss machine learning based algorithms that solve the first step of vision-based autonomous systems i.e., vision based pose estimation. This paper presents a critical review in advancements of 6D pose estimation using both 2D and 3D input data, and compare how they deal with the challenges shared by the computer-vision based localisation problem. We also look over algorithms with their applications in space based tasks like in-orbit docking, rendezvous and the challenges that come with space-vision applications. To conclude the review we also highlight niche problems and possible avenues for future research.