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 | 1 | initial version |
See [here] (https://github.com/mavlink/mavros/issues/516) for more details about the solution I am trying to use... Below is in brief:
In order to get relevant covariance information, I am merging the IMU, published by mavros, with the OpticalFlowRad msgs, transformed in a TwistwithcovarianceStamped by optflow_odometry. The covariance is derived from the image quality of the px4flow. The operation is handled by [robot_localization] (http://wiki.ros.org/robot_localization).
This gives me a proper sensor based odometry. Then I use another EKF to fuse this odometry with the position published by my localization nodes.
Do you think this workflow is valid?
| | 2 | No.2 Revision |
See [here] (https://github.com/mavlink/mavros/issues/516) here for more details about the solution I am trying to use... Below is in brief:
In order to get relevant covariance information, I am merging the IMU, published by mavros, with the OpticalFlowRad msgs, transformed in a TwistwithcovarianceStamped by optflow_odometry. The covariance is derived from the image quality of the px4flow. The operation is handled by [robot_localization] (http://wiki.ros.org/robot_localization).robot_localization.
This gives me a proper sensor based odometry. Then I use another EKF to fuse this odometry with the position published by my localization nodes.
Do you think this workflow is valid?
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