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Spacecraft Swarm Guidance Using a Sequence of Decentralized Convex Optimizations

机译:使用一系列分散凸优化的航天器群引导

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摘要

This paper presents partially decentralized path planning algorithms for swarms of spacecraft composed of hundreds to thousands of agents with each spacecraft having limited computational capabilities. In our prior work, J2-invariant orbits have been found to provide collision free motion for hundreds of orbits. This paper develops algorithms for theudswarm reconfiguration which involves transferring from one J2-invariant orbit to another avoiding collisions and minimizing fuel. To perform collision avoidance, it is assumed that the spacecraft can communicate their trajectories with each other. The algorithm usesudsequential convex programming to solve a series of approximate path planning problems until the solution converges. Two decentralized methods are developed: a serial method where the spacecraft take turn updating their trajectories and a parallel method where all of the spacecraft update their trajectories simultaneously.
机译:本文提出了由数百到数千个代理组成的航天器群的部分分散路径规划算法,每个航天器的计算能力有限。在我们先前的工作中,发现J2不变轨道可为数百个轨道提供无碰撞运动。本文开发了“超温”重构算法,该算法涉及从一个J2不变轨道转移到另一个J2不变轨道,以避免碰撞并最大程度地减少燃料。为了避免碰撞,假设航天器可以相互传达其轨迹。该算法使用后序凸规划来解决一系列近似路径规划问题,直到解收敛为止。开发了两种分散方法:一种是串行方法,其中航天器轮流更新其轨迹;另一种是并行方法,其中所有航天器均同时更新其轨迹。

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