具有学习和推理能力的空间无人系统智能架构

Intelligent architecture of space unmanned system with learning and reasoning capabilities

以卫星、飞船、深空探测器为代表的航天器是一类典型的无人系统,经历了从自动化到自主化的不断发展.为提升航天器对未知空间环境和复杂空间任务的适应能力和智能自主水平,以空间无人系统为研究对象设计了具有学习和推理能力的无人系统智能架构,给出架构的组成及功能;接着分析该架构中学习和推理能力的运作机制,并针对架构所需的动作库和知识库的构建、更新与扩展方法等关键技术提出解决方案;最后通过地外星表巡视采样任务示例,具体说明在该智能架构下的新知识生成、基于知识的推理和自主执行任务的过程,以及过程中知识库、环境、任务和动作库之间的交互关系.

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.