Abstract:  Aiming at the characteristics of the guidance, navigation and control (GNC) system of the lunar rendezvous and docking, a safety auxiliary prediction system based on the humanmachine collaboration frame is designed. The system includes two parts: building the rendezvous and docking safety rule knowledge base by the machine learning method, and predicting the safety by the use of the base. Firstly, in the ground semiphysical simulation test environment, the features are extracted and matched, while the object is imaged by the navigation surveillance camera. And then, the matched features and rendezvous and docking bias are used to form the training samples pairs. Secondly, the safety rules knowledge base is used to predict the safety of the subsequent process rendezvous and docking, according to the image of current state, and obtain the probability of success. The semiphysical experiments on the ground show that the system can improve the intelligence level in the flight control process and give effective data and monitoring support for the ground flight controllers.

Key words: rendezvous and docking, visual navigation, humanmachine collaboration, safety prediction