Title :
A sensor-centric EKF for inertial-aided visual odometry
Author :
Kleinert, Moritz ; Stilla, Uwe
Author_Institution :
Fraunhofer IOSB, Ettlingen, Germany
Abstract :
When appropriate infrastructure is not available, localization of pedestrians becomes a difficult task. This is especially the case in urban or indoor scenarios, where satellite navigation is hindered due to occlusions or multipath effects. A promising alternative is to combine a small, low-cost inertial measurement unit (IMU) with a camera in order to exploit the complementary error characteristics of these devices by simultaneously estimating the positions of observed landmarks and the trajectory of the sensor system with a stochastic filter.
Keywords :
Kalman filters; computational complexity; distance measurement; image sensors; inertial navigation; nonlinear filters; pedestrians; EKF; IMU; SLAM; camera; computational complexity; extended Kalman filter; indoor scenarios; inertial-aided visual odometry; jacobians; low-cost inertial measurement unit; monocular simultaneous localization and mapping; multipath effects; observed landmarks; occlusions; pedestrians localization; satellite navigation; sensor system trajectory; sensor-centric EKF; sensor-centric formulation; state prediction equations; stochastic filter; urban scenarios; Cameras; Covariance matrices; Equations; Mathematical model; Navigation; Simultaneous localization and mapping; Vectors;
Conference_Titel :
Indoor Positioning and Indoor Navigation (IPIN), 2013 International Conference on
Conference_Location :
Montbeliard-Belfort
DOI :
10.1109/IPIN.2013.6817915