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首页> 外文期刊>Acta astronautica >Large-scale object selection and trajectory planning for multi-target space debris removal missions
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Large-scale object selection and trajectory planning for multi-target space debris removal missions

机译：多目标空间碎片清除任务的大规模目标选择和轨迹规划

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摘要

Upcoming active space debris removal missions will most likely attempt to remove several objects per mission. The design of such missions involves the selection of the objects to be removed, as well as the optimisation of the visit sequence and the orbital transfers interconnecting them. In this work a branch-and-bound-based algorithm is presented for the preliminary design of multi-target space debris removal missions. The proposed algorithm comprises two different levels. The upper level, modelled as an Integer Linear Programming problem, deals with the combinatorial complexity of the problem. The lower level, modelled as a Mixed Integer Nonlinear Programming problem, encapsulates the orbital dynamics. Throughout the problem resolution, the upper level selects promising subsets of a pool of candidate objects of space debris, so that a removed threat value is maximised. Each of these subsets is passed through to the lower level, which ensures that there is a feasible trajectory that allows to rendezvous, in a specific sequence, with each and every object in the subset, while prescribed mission duration and v constraints are fulfilled. This framework is able to exploit the structure of the problem so that instances with large pools of candidate objects can be efficiently solved while achieving the certificates of optimality that branch-and-bound methods provide.
机译：即将进行的活动空间碎片清除任务很可能会在每次任务中尝试清除几个物体。这种飞行任务的设计包括选择要移除的物体，以及优化访问顺序和将它们互连的轨道转移。在这项工作中，提出了一种基于分支定界的算法，用于多目标空间碎片清除任务的初步设计。所提出的算法包括两个不同的层次。上层建模为整数线性规划问题，处理该问题的组合复杂性。较低层被建模为混合整数非线性规划问题，它封装了轨道动力学。在整个问题解决过程中，高层选择空间碎片候选对象池的有希望的子集，以便最大程度地消除威胁值。这些子集中的每个子集都传递到较低的级别，从而确保存在一条可行的轨迹，该轨迹允许以特定的顺序与子集中的每个对象集合，同时满足规定的任务持续时间和v约束。该框架能够利用问题的结构，从而在获得分支定界方法提供的最佳证书的同时，可以有效地解决具有大量候选对象的实例。

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