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.
Real-Time Autonomous Spacecraft Proximity Maneuvers and Docking Using an Adaptive Artificial Potential Field Approach / Zappulla, R.; Park, H.; Virgili-Llop, J.; Romano, M.. - In: IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY. - ISSN 1063-6536. - 27:6(2019), pp. 2598-2605. [10.1109/TCST.2018.2866963]
Real-Time Autonomous Spacecraft Proximity Maneuvers and Docking Using an Adaptive Artificial Potential Field Approach
Romano M.
2019
Abstract
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.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2963430