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Improved Monte Carlo Tree Search-based approach to low-thrust multiple gravity-assist trajectory design

  • School of Astronautics, Harbin Institute of Technology
  • University of Pisa

Research output: Contribution to journalArticlepeer-review

Abstract

In the preliminary design of low-thrust trajectories with multiple gravity-assist phases, the selection of the celestial bodies to be considered and the sequence of optimal maneuvers have a significant impact on the overall mission performance. This aspect makes the preliminary transfer trajectory analysis a very complex task. This Short Communication presents a novel method to design heliocentric multiple gravity-assist transfer trajectories for a spacecraft with a low-thrust propulsion system, where the total velocity variation is minimized. In this context, a Bézier shape-based method is used to describe the generic arc of a propelled trajectory, while an extension of the Monte Carlo Tree Search algorithm is used for a rapid analysis of the gravity-assist maneuver sequence. In particular, the proposed approach effectively solves the problem of selecting a suitable balance parameter in the Monte Carlo Tree Search-based routines, which makes the method especially useful in a preliminary mission phase. The effectiveness of the proposed approach is shown by simulating an interplanetary transfer towards the outer regions of the Solar System.

Original languageEnglish
Article number107946
JournalAerospace Science and Technology
Volume130
DOIs
StatePublished - Nov 2022
Externally publishedYes

Keywords

  • Bézier shape-based method
  • Low-thrust trajectory design
  • Monte Carlo Tree Search method
  • Multiple gravity-assist trajectory

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