Abstract There are always various uncertainties in a deep space exploration mission, which induce a significant impact on plan execution and may cause plan failures. In such case, remote control from the Earth is too late to handle that problem in time, because of the long distance between the probe and the ground station. Therefore, an autonomous reactive plan repair strategy RPRS (Reactive Plan Repair Strategy) for deep space missions is proposed, which enables the probe to recover autonomously and quickly from plan failures with unsatisfactory resources or logical conditions without human intervention. In this strategy, the concept of forwarding dock state is defined to effectively manage the temporal information of planned actions and fortuitous events during execution, to support the repair work of subsequent GRDR (Global Resource Diagnosis & Repair algorithm) and TDPR (Tiny Deviation Plan Repair search algorithm). This strategy iteratively performs a search on the forwarding dock state whenever the original plan fails, i.e., a shortage of resources or invalid logical conditions, and is tested empirically to demonstrate the efficiency and effectiveness with enough domain knowledge.

    Highlights RPRS enables the deep space probe to autonomously react to plan failures when executed. GRDR detects a shortage of resources for the mission plan and solves it. TDRP effectively handles unsatisfactory logic conditions of the mission plan. The Martian rover model performs well under vary types of plan failures.


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    Titel :

    RPRS: a reactive plan repair strategy for rapid response to plan failures of deep space missions


    Beteiligte:
    Chen, Chao (Autor:in) / Xu, Rui (Autor:in) / Zhu, Shengying (Autor:in) / Li, Zhaoyu (Autor:in) / Jiang, Huiping (Autor:in)

    Erschienen in:

    Acta Astronautica ; 175 ; 155-162


    Erscheinungsdatum :

    2020-05-05


    Format / Umfang :

    8 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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