Visual sensors have a major advantage over traditional sensing methods for navigation in unknown environments since they provide rich information about the environment. However, they do not offer direct navigation measurements, and the images must be pre-processed. To extract meaningful information, the development of reliable and computationally efficient algorithms are required. This study presents a visual odometry solution that can effectively operate to estimate the pose of a small lander for the soft moon landing. For this purpose, an algorithm is designed to estimate the angular and translational velocities of the spacecraft during the descent and landing phases. A Kalman filter-based algorithm is proposed, which uses the dual quaternion formulation to provide a linear Kalman filter for velocity estimation. The proposed algorithm is tested in a simulation environment for a lunar landing scenario.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Dual Quaternion Based Visual Odometry Method for a Lunar Lander


    Contributors:


    Publication date :

    2024-03-02


    Size :

    2741152 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Virtual Trajectory Augmented Landing Control Based on Dual Quaternion for Lunar Lander

    Kwon, Jae-Wook / Lee, Donghun / Bang, Hyochoong | AIAA | 2016



    VISUAL ODOMETRY FOR PRECISION LUNAR LANDING

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


    Visual odometry with depth-wise separable convolution and quaternion neural networks

    De Magistris G. / Comminiello D. / Napoli C. et al. | BASE | 2023

    Free access