Current methods for pose and shape estimation of small bodies, such as comets and asteroids, rely on extensive ground support and significant use of radiometric measurements using the Deep Space Network. The Stereo-Photoclinometry (SPC) technique is currently used to provide detailed topological information about a small body as well as its absolute orientation and position. While this technique has produced very accurate estimates, the core algorithm cannot be run in real-time and requires a team of scientists on the ground who must communicate with the spacecraft in order to oversee SPC operations. Autonomous onboard navigation addresses these limitations by eliminating the need for human oversight. In this paper, we present an optimization-based estimation algorithm for navigation that allows the spacecraft to autonomously approach and maneuver around an unknown small body by mapping its geometric shape, estimating its orientation, and simultaneously determining the trajectory of the center of mass of the small body. We show the effectiveness of the proposed algorithm using simulated data from a previous flight mission to Comet 67P.


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    Title :

    Autonomous Small Body Mapping and Spacecraft Navigation


    Contributors:

    Publication date :

    2018-10-01


    Type of media :

    Preprint


    Type of material :

    No indication


    Language :

    English





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