Abstract:

In order to improve the efficiency of dynamic planning processing for inspectors in deep space exploration missions, a knowledge modeling method and dynamic planning process are proposed for inspectors based on practical experience in aerospace engineering, combined with the theoretical research results of hierarchical task network (HTN). To address the issue of classical action planning systems not being able to handle temporal constraint relationships, a representation method for constrained state events is introduced in modeling. To address the temporal constraints in dynamic programming, the definition of Allen interval algebra is extended, and a temporal logic judgment method for events, global time points, and virtual events is proposed. A method for virtual instructions to inherit the original state space is proposed to address the issue of state space consistency in dynamic planning. The research results have improved the knowledge modeling method of HTN in the aerospace field, solved the defect of lack of time information constraints in classical action planning. The proposed virtual events and virtual instructions to solve dynamic planning state judgment can effectively improve the work efficiency of remote operation of the inspector in deep space exploration tasks and the flexibility of event processing in the ground center.

Key words: hierarchical task network (HTN), dynamic programming, virtual instruction, teleoperation