Single-satellite autonomous task planning method based on intelligent optimization and constraint reasoning
An intelligent optimization algorithm and technology for autonomous tasks, applied in the field of remote sensing satellites, can solve problems such as complex planning problems, achieve good mission planning results, less computational effort, and facilitate continuous updating.
Active Publication Date: 2018-07-27
FOSHAN UNIVERSITY +1
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The planning problem becomes more complex if these factors are taken into account when searching
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[0025] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with specific examples. It should be understood that these descriptions are exemplary only, and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.
[0026] The single-satellite autonomous task planning method based on intelligent optimization and constraint reasoning of the present invention adopts a method combining an intelligent optimization algorithm and a reasoning engine to solve the framework. The intelligent optimization algorithm includes a task sorting step, a task decomposition step and an activity opportunity search step, the task sorting step includes sorting the tasks according to the selected sorti...
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The invention discloses a single-satellite autonomous task planning method based on intelligent optimization and constraint reasoning. According to the method, an intelligent optimization algorithm and an inference engine are combined for solving a framework. The intelligent optimization algorithm comprises a task sequencing step, a task decomposition step and an activity opportunity searching step. The task decomposition step is used for decomposing sorted tasks into the structured or partial sequence of an activity diagram. The activity opportunity searching step is used for scheduling an imaging sub-task and an imaging direction adjusting sub-task to obtain a quasi-optimal solution. The inference engine is used for carrying out conflict checking on the quasi-optimal solution based on the logic relation, time and satellite resource constraints in the activity diagram. If the conflict exists, the quasi-optimal solution is optimized according to the conflict situation. Meanwhile, the local searching is carried out on the optimized quasi-optimal solution, so that the quasi-optimal solution is obtained again. After that, the conflict checking is carried out again until the verification result of the conflict is passed or the set maximum number of iterations is reached. According to the method, a better task planning result is generated by using less calculation amount.
Description
technical field [0001] The invention relates to the technical field of remote sensing satellites, in particular to a single-satellite autonomous mission planning method based on intelligent optimization and constraint reasoning. Background technique [0002] With the improvement of imaging satellite hardware level, its application target has higher requirements. Because of complex constraints, unpredictable state information and complex requirements, satellite mission planning has always been a difficult point in the field of systems engineering. [0003] On-board autonomous mission planning means that it rarely relies on external information injection and control. Smart satellites independently plan and schedule information acquisition activities of satellite resources according to their perceived state and external environment, and formulate satellites that meet the needs of satellite application tasks. Earth Observation Programme. [0004] The autonomous management of i...
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IPC IPC(8): G05B13/04G06N5/04
CPCG05B13/042G06N5/04
Inventor 何敏藩邢立宁白国庆石建迈王锐谭旭文翰熊彦甘文勇陈剑
Owner FOSHAN UNIVERSITY