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Many recent researches have been studying techniques to handle the problem of pose and shape reconstruction in the framework of space proximity operations. The most challenging scenario is when the target satellite is uncooperative, i.e., out of control, and possibly of unknown shape because of damages occurred to its structure. In such a situation, complete awareness of the target's configuration is mandatory and can be achieved through optical hardware. Moreover, recent studies have shown how passive optical sensors are so far the best choice when limitations of mass and power consumption on board the chaser satellite are considered. Monocular cameras, if complemented with a single depth information (e.g., provided by a range-finder), can be used to extract meaningful information of the observed satellite. When paired with purposely built filtering algorithms, the accuracy reached by such systems can increase considerably. In this work, a navigation algorithm exploiting images acquired by a camera is included in a GNC architecture, aimed to perform a rendezvous to the target satellite. The navigation algorithm consists of the following blocks: an image features extraction and matching block, tuned to track features for as long as possible; a features sorting and storing routine, used to rearrange features in a usable way; a UKF filter, which is fed up with features' location on the image plane and range distance, and returns the estimates of relative position, velocity, attitude, angular velocity along with the target reconstructed shape. From the operational point of view, firstly the possible docking area is identified from the acquired images. Then, after an initial phase in which the navigation blocks estimates the relative pose and shape, the reference approaching trajectory is computed through an optimization procedure carried out by means of an inverse method. The trajectory is parameterized through a polynomial basis and a gradient method is applied to seek for a minimum of the fuel consumption, under constraints such as collision avoidance and continuous visibility. The main contribution of this research resides in the integration of visual navigation with optimal guidance. In fact, iterative successful calculation of the optimal trajectory is exclusively possible if an accurate estimate of target satellite's relative pose and shape is available. The GNC architecture is tested with a co-simulation approach, in which the orbital dynamics, navigation filtering and control laws are developed in MATLAB, while synthetic images are rendered and imported in closed-loop from Blender. Different dynamical states of the target are considered to analyze the robustness of the proposed architecture and to highlight its operational limitations. • Monocular images used to reconstruct pose and shape of an uncooperative target. • KAZE features and Kanade–Lucas–Tomasi tracker used to acquire measures from images. • Estimated pose and shape used to compute optimal, collision-free rendezvous path. • Optimal path followed in closed-loop by using reconstructed pose and shape. • Algorithm tested with co-simulation. Blender used to render images in closed-loop. [ABSTRACT FROM AUTHOR]

Abstract Performing rendezvous in close-proximity of a non-cooperative target is a challenging task, especially if certain performance requirements have to be met. When maneuvering in hazardous scenarios in order to accomplish either refuelling, inspection, repair or dismissal tasks, optimality and safety are relevant aspects to be sought. Additionally, autonomy is essential in unmanned missions. All these aspects can be achieved through purposely intended Guidance Navigation and Control (GNC) architectures. Optimality is obtained by means of the guidance system, that is by a proper optimal trajectory calculation. Safety and accuracy are guaranteed by evaluation of target's relative pose and shape, which is exploited by the navigation system. Among all the possible choices, optical hardware is becoming widely studied for its high accuracy and capability to reconstruct three-dimensional properties of the observed scene. The present work investigates the reciprocal influences between the guidance and navigation subsystems, putting higher focus on how the performance of an optimal rendezvous maneuver with a non-cooperative target can be influenced by the accuracy reached in the pose and shape estimation process. To this purpose, the chaser, or maneuvering spacecraft is considered to be equipped with a single camera and a distance sensor, as this architecture both provides high accuracy and meets mass, power and volume requirements to be implemented on-board a small platform. An algorithm including the optimization process and a purposely built filter, capable of receiving images as inputs and providing evaluation of target's relative pose and shape as output, is implemented and tested in several different scenarios to validate the feasibility of the maneuver. Highlights • Feasibility of a rendezvous autonomous maneuver with a non-cooperative target is assessed. • A camera is used to reconstruct target's pose and shape by features' detection and matching. • An inverse optimization method is employed to compute a trajectory which minimizes Delta V. • The performance of the adopted approach are evaluated through several simulations. [ABSTRACT FROM AUTHOR]