Attitude navigation for deep space explorer based on mission planning

Fanyu Zhao, P. Cui, Rui Xu, Z. Li
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Abstract

In deep space exploration, unknown environment require the real-time controlling on an explorer, however the time delay of communication and signal blocking by stars make it impossible for the explorer to achieve real-time controlling. In order to solve the real-time attitude controlling problem for deep space explorers, the characteristics of complex system structure, coupling constraints, and parallel computing were considered. This paper used a method based on status and timeline to describe the deep space exploration domain knowledge, proposed a mission planning method based on multiple constraints satisfaction to realize the automatic generation of the on-board attitude maneuver missions. Including several kinds of geometrical constraints, dynamic constraints, and kinematic constraints, the constraints existing in the attitude maneuver process of an explorer has been considered and an attitude maneuver planning approach was used, which guaranteed the safety of the explorer system in the maneuver. Mission consequences could be generated from the mission planning approach as the high level commands for the attitude controlling system on-board, which could guide the attitude controlling system to complete the attitude maneuver missions automatically and safely in the mission level.
基于任务规划的深空探测器姿态导航
在深空探测中,未知环境要求探测器对未知环境进行实时控制,但通信的时延和恒星对信号的阻挡使得探测器无法实现实时控制。为了解决深空探测器的实时姿态控制问题,考虑了系统结构复杂、耦合约束和并行计算的特点。采用基于状态和时间线的深空探测领域知识描述方法,提出了一种基于多约束满足的任务规划方法,实现了星上姿态机动任务的自动生成。考虑了探测器姿态机动过程中存在的几种几何约束、动力学约束和运动学约束,采用姿态机动规划方法,保证了探测器系统在机动过程中的安全。任务规划方法可以生成任务结果,作为星载姿态控制系统的高层指令,指导姿态控制系统在任务级自动安全完成姿态机动任务。
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