Abstract Small Celestial Bodies (SCBs) like Near Earth Asteroids (NEAs) as potential destinations for in-situ resource utilization form an integral part of establishing a sustainable human presence beyond the cis-lunar space. Autonomous navigation and distributed spacecraft architecture have been widely recognized as the most crucial technologies essential for executing sophisticated mission tasks in the proximity of these bodies. Current semi-autonomous methods used for proximity navigation require an initial mapping phase and ground intervention that are impediments for large scale missions envisioned for the future. This paper presents a method based on Simultaneous Localization and Mapping (SLAM) for a fully autonomous navigation of distributed spacecraft in SCB orbits. The spacecraft initially navigate independently using SLAM in separate local frames. Once sufficient landmarks have been encountered by the spacecraft, a map merging process that utilizes the common landmarks observed by all the spacecraft as pivots is invoked to consolidate the navigation models and state estimates from all the spacecraft in a common frame. The navigation process then proceeds in this common frame. The utility of the algorithm is assessed with a simulation experiment considering two spacecraft in orbit around a NEA. The results from the simulation indicate the suitability of the proposed method for proximity navigation and its prospects for further development.

    Highlights Autonomous navigation of distributed spacecraft in small celestial body orbits. Replaces photoclinometry based navigation for in-situ resource utilization missions. Application of SLAM for proximity navigation near asteroids. Feature based map merging method to enable coordinated spacecraft navigation. Enables autonomous mission planning for asteroid missions.


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    Titel :

    Probabilistic approach to the autonomous navigation of distributed spacecraft near small celestial bodies


    Beteiligte:

    Erschienen in:

    Acta Astronautica ; 182 ; 517-530


    Erscheinungsdatum :

    2021-01-22


    Format / Umfang :

    14 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch






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