2 research outputs found
Experimental Evaluation of a Visual-Inertial Navigation System with Guaranteed Convergence
This contribution presents a constraints-based loosely-coupled Augmented Implicit Kalman
Filter approach to vision-aided inertial navigation that uses epipolar constraints as output
map. The proposed approach is capable of estimating the standard navigation output (ve-
locity, position and attitude) together with inertial sensor biases. An observability analysis
is proposed in order to define the motion requirements for full observability of the system
and asymptotic convergence of the parameter estimates. Simulations and experimental
results are summarized that confirm the theoretical conclusions