
This paper introduces a faster and more accurate version of the Multi-State Constraint Kalman Filter (MSCKF) for visual-inertial odometry, called FMSCKF, which strategically manages feature extraction and state pruning to reduce computational cost without sacrificing accuracy.


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fast-multi-state-constraint-kalman-filter-for-improved-visual-inertial-odometry


Fast Multi-State Constraint Kalman Filter for Improved Visual-Inertial Odometry


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DynaVINS++ improves the robustness of visual-inertial state estimation in dynamic environments, particularly addressing challenges posed by abruptly dynamic objects, by introducing Adaptive Truncated Least Squares for outlier rejection and a Stable State Recovery mechanism based on bias consistency checks.


dynavins-enhancing-visual-inertial-state-estimation-in-dynamic-environments-using-adaptive-truncated-least-squares-and-stable-state-recovery


DynaVINS++: Enhancing Visual-Inertial State Estimation in Dynamic Environments Using Adaptive Truncated Least Squares and Stable State Recovery
