Centralized visual based navigation and control of a swarm of satellites for on-orbit servicing

The current growing interest into on-orbit proximity operations motivates the effort in designing mission architectures able to fulfill on-orbit operations. Small satellites are appealing in terms of costs, effectiveness and realization, but present intrinsic power and mass limitations and are only equipped with basic instrumentation. However, it is possible to envisage not just one, but a fleet or swarm of small satellites which cooperate to reach a certain goal. In our research, a swarm of small satellites (called “Children S/C”), deployed from a larger platform (called “Mother S/C”), is employed in the inspection of a damaged spacecraft, which cannot be directly approached by the Mother S/C for safety reasons. To this purpose, because of power and mass limitations on each Child S/C, the navigation process is delegated to the Mother S/C, that is equipped with a passive camera, chosen for its capability to provide accurate and complete description of the observed scene. A navigation algorithm runs on the Mother S/C, which identifies and tracks the Children S/C framed in the scene, even though false matches (i.e., incorrect tracking of a given child) could happen. The navigation algorithm is made robust through the generation at each time step of a propagated virtual image (based on the previous estimate of the swarm state) which is compared to the acquired image for the correct identification of each child. When the relative position estimates reach a satisfactory accuracy, the Mother S/C communicates to the Children S/C their current state and an optimal impulsive control strategy can be implemented to make the swarm fulfill the required task. In our scenario, as an example of a possible application, the children aim to reach a closed relative orbit around the target, with the goal to simultaneously observe it from equally spaced points of view. Simulations are carried out in a purposely developed software environment, in which images of rendered CAD models are acquired and processed to have a realistic validation of the estimation algorithm, showing satisfactory performance and robustness for the overall mission accomplishment.