Abstract

Spacecraft represented by satellites, manned spaceships, and deep space probes are typical unmanned systems that are developing from automation to autonomy. To improve the adaptability and intelligent autonomy level of spacecraft to unknown space environments and complex space tasks, an intelligent architecture of space unmanned system with learning and reasoning capabilities is designed and the architectural components and functions are proposed. Then, the operating mechanism of learning and reasoning capabilities in the architecture are analyzed, and the solutions for key technologies, such as the construction, update, and expansion methods of the action and knowledge libraries, are proposed. Finally, through an example of the extraterrestrial surveying and sampling task, the process of new knowledge generation, knowledge-based reasoning, and autonomous task execution under this intelligent architecture, as well as the interaction between the knowledge library, environment, task, and action library, are explained.

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