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Try using robot_pose_ekf package and make sure that the frame_id of IMU is changed to base_footprint. Using the ROBOT_POSE_EKF package , a Extended Kalman Filter can be applied to IMU and Visual Odometry data..I guess that you wont have any problem with the covariances by using this package..

Try using robot_pose_ekf package and make sure that the frame_id of IMU is changed to base_footprint. Using the ROBOT_POSE_EKF package , a Extended Kalman Filter can be applied to IMU and Visual Odometry data..I guess that you wont have any problem with the covariances by using this package..

Also there is another package called ethzasl_sensor_fusion which takes in "pose" information and fuses with IMU information. There are tutorials on how to use this package too.

good luck

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