Extended State-Based Planning Approach for Deep Space Exploration

Hao Jin; Rui Xu; Wenming Xu; Shengying Zhu

doi:10.1109/TAES.2019.2920046

Extended State-Based Planning Approach for Deep Space Exploration

Hao Jin^*, Rui Xu, Wenming Xu, Shengying Zhu

^*Corresponding author for this work

School of Aerospace Engineering

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

This paper deals with a new modeling method and a powerful planning approach for deep space probes. The key technique is based on the concept of extended state model. Furthermore, extended state model planning (ESMP) algorithm is designed to be fully compliant with the model, and flaw selection strategies are proposed to avoid redundant work. Finally, we discuss the time complexity of ESMP, and computational results comparing ESMP with the algorithm in Europa are presented.

Original language	English
Article number	8726160
Pages (from-to)	645-659
Number of pages	15
Journal	IEEE Transactions on Aerospace and Electronic Systems
Volume	56
Issue number	1
DOIs	https://doi.org/10.1109/TAES.2019.2920046
Publication status	Published - 1 Feb 2020

Keywords

Deep space probe
knowledge model
mission planning
search algorithm

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10.1109/TAES.2019.2920046

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KW - search algorithm

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Extended State-Based Planning Approach for Deep Space Exploration

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Keywords

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