Motion Estimation from Image and Inertial Measurements

Abstract

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Towards Consistent Vision-Aided Inertial Navigation

“…Numerous VINS approaches have been presented in the literature, including methods based on the Extended Kalman Filter (EKF) [3,17,26], the Unscented Kalman Filter (UKF) [7], and Batch-least Squares (BLS) [32]. Non-parametric estimators, such as the Particle Filter (PF), have also been applied to visual odometry (e.g., [6,33]).…”

Vision-Aided Inertial Navigation for Precise Planetary Landing: Analysis and Experiments

“…Figs. [5][6][7][8] show that the filter estimates for these variables are consistent, indicating that the attitude estimates are also consistent. The filter attitude estimate was further verified through an independent measurement of the final attitude at touchdown using a compass.…”

“…The standard method of treating such features is to include their positions in the state vector, and to estimate them along with the camera trajectory. This is the well-known Simultaneous Localization and Mapping (SLAM) problem, for which numerous approaches that employ vision and inertial sensing have recently been proposed (e.g., [8] and references therein). However, the need to maintain the landmark estimates in SLAM results in increased computational complexity (quadratic in the number of features for EKF-SLAM).…”

Efficient Online Egomotion Estimation Using Visual and Inertial Readings

“…For instance, [15] and [1] use Kalman filters (or Kalman filter extensions) to integrate measurements produced by both their measurement devices whereas [16] and [17] use Kalman filters to estimate egomotion, inertial readings, estimation errors and the 3D coordinates of all known features. The latter approach seems somewhat out of place in the context of this work, i.e.…”