Research/ ORBITAL ROBOTICS
Convolutional neural network-based spacecraft attitude control for docking port alignment
Sanghyeon Kim, Han-lim Choi A
Guidance, Dynamics & ControlOpenAlex keyword: spacecraft attitude control · Learning-based MethodsOpenAlex topic: Reinforcement Learning in Robotics · Rendezvous, Proximity Ops & DockingOpenAlex keyword: spacecraft docking
This paper proposes the spacecraft attitude control algorithm based on Convolutional Neural Networks (CNNs) for spacecraft's docking port alignment. the CNN model is used in order to recognize the attitude of target spacecraft and the attitude controller aligns the docking port of the target spacecraft using the target spacecraft's attitude information obtained from CNN. Three-Dimensional spacecraft simulator is developed for training CNN model and testing the algorithm. Experiments are conducted for demonstrating the target spacecraft's attitude recognition and attitude control performances of the proposed algorithm.