A novel sequential information filter formulation for computationally efficient visual-inertial odometry and mapping is developed in this work and applied to a realistic moon landing scenario. Careful construction of the square-root information matrix, in contrast to the full information or covariance matrix, provides easy and exact mean and covariance recovery throughout operation. Compared to an equivalent extended Kalman filter implementation, which provides identical results, the proposed filter does not require explicit marginalization of past landmark states to maintain constant-time complexity. Whereas measurements to opportunistic visual features only provide relative state information, resulting in drift over time unless a priori mapped landmarks are identified and tracked, the tight coupling of the inertial measurement unit provides some inertial state information. The results are presented in a terrain-relative navigation simulation for both a purely orbital case (with no active propulsion) and a landing case with a constant thrust.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Square-Root Extended Information Filter for Visual-Inertial Odometry for Planetary Landing


    Contributors:

    Published in:

    Publication date :

    2022-10-06


    Size :

    15 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    RADAR AIDED VISUAL INERTIAL ODOMETRY INITIALIZATION

    NIESEN URS | European Patent Office | 2019

    Free access

    VISUAL ODOMETRY FOR PRECISION LUNAR LANDING

    Molina, Giovanni / Hansen, Michael / Getchius, Joel et al. | Springer Verlag | 2024


    Radar aided visual inertial odometry initialization

    NIESEN URS | European Patent Office | 2020

    Free access


    RADAR AIDED VISUAL INERTIAL ODOMETRY OUTLIER REMOVAL

    NIESEN URS | European Patent Office | 2019

    Free access