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Real-Time Autonomous Spacecraft Proximity Maneuvers and Docking Using an Adaptive Artificial Potential Field Approach

机译:使用自适应人工势场方法的实时自主航天器接近操纵和对接

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In an effort to pursue more advanced missions in space, improved on-board trajectory optimization and path (re)planning capabilities are necessary. Over the past decades, numerous missions have pushed the state of the art in autonomous rendezvous and proximity operations (RPOs). Regardless of the mission, any RPO guidance algorithm must be able to react to a dynamic environment while generating a fuel-efficient trajectory. An adaptive artificial potential function (AAPF) guidance exhibiting these properties has been experimentally evaluated on a spacecraft air-bearing test bed and its performance compared to traditional APF and other real-time guidance methods.
机译:为了追求更高级的太空任务,必须改进机载轨迹优化和路径(重新)计划能力。在过去的几十年中,无数的任务推动了自主会合和近距离作战(RPO)的最新发展。无论执行何种任务,任何RPO引导算法都必须能够对动态环境做出反应,同时生成省油的轨迹。展示了这些特性的自适应人工势能(AAPF)制导已经在航天飞机的空气测试台上进行了实验评估,其性能与传统APF和其他实时制导方法相比。

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