Ricerc@Sapienza

In the near future Autonomous Robotic Systems (ARSs) will be playing an increasingly important role in space applications such as inspecting, repairing, refuelling and re-orbiting spacecraft. Recent interest into on-orbit proximity operations has pushed towards the development of autonomous Guidance, Navigation and Control (GNC) strategies. The proposed research will focus on each of these three aspects, with the goal of verifying innovative solutions. In particular, stereo vision navigation enables a wide variety of possibilities as it can provide information not only about the kinematic state, but also about the shape of the observed object. This technique relies on the acquisition and matching of the images taken from two cameras, on-board the ARS, in order to estimate the relative kinematic state between the ARS and a non-cooperative target satellite. The process of state estimation is carried out by means of a Kalman filter, which refines the state estimate in real time by merging the measurements taken from the images with the state propagation. Knowing the relative position, attitude and velocities with a certain degree of accuracy is of crucial importance for the ARS to track an optimal trajectory (output of the guidance block) in terms of propellant consumption and target¿s illumination conditions. At the scope of tracking this trajectory, a special application of the Impedance Control (IC) is proposed. This control algorithm is mainly applied to contact operations, with the goal of making the system behave as a mass-spring-damper group so to provide a compliant behaviour in response to an external forcing action. In the proposed version of the IC, the forcing term is replaced by a virtual force generated whenever the servicing spacecraft deviates from the reference trajectory. The final output of the research is to test and validate the described combination of stereo vision, optimal path planning and IC both from the numerical and experimental standpoint.