A deep learning strategy for on-orbit servicing via space robotic manipulator
Autonomous robotic systems are currently being addressed as a critical element in the development of present and future on-orbit operations. Modern missions are calling for systems capable of reproducing human’s decision-making process thus enhancing their performance. Generally, space manipulators are mounted on a floating spacecraft in a microgravity environment, consequently leading to a mutual influence between the robotic arms and the platform dynamics, thus making the motion planning and control design more challenging than those of terrestrial robots.