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1 | initial version |
However, when i control the robot platform spin around many times, the error between package output and real path increases.
An error in the platform spin might be related to a misconfiguration of the covariance. I am thinking about a too slow convergence of the filter. Do you have better results when the spinning is slow?
the accuracy of output increased a lot when you add GPS sensor.
GPS sensor is not the best sensor to improve your rotation accuracy. Have you thought about the Madgwick filter?
Why odom/filter are not more accuracy than odom/imu?
It all depends on the covariances of the measurements and of the predictions.
Accuracy
2 | No.2 Revision |
However, when i control the robot platform spin around many times, the error between package output and real path increases.
An error in the platform spin might be related to a misconfiguration of the covariance. I am thinking about a too slow convergence of the filter. Do you have better results when the spinning is slow?
the accuracy of output increased a lot when you add GPS sensor.
GPS sensor is not the best sensor to improve your rotation accuracy. Have you thought about the Madgwick filter?
Why odom/filter are not more accuracy than odom/imu?
It all depends on the covariances of the measurements and of the predictions.
Accuracy
3 | No.3 Revision |
However, when i control the robot platform spin around many times, the error between package output and real path increases.
An error in the platform spin might be related to a misconfiguration of the covariance. I am thinking about a too slow convergence of the filter. Do you have better results when the spinning is slow?
the accuracy of output increased a lot when you add GPS sensor.
GPS sensor is not the best sensor to improve your rotation accuracy. Have you thought about the Madgwick filter?
Why odom/filter are not more accuracy than odom/imu?
It all depends on the covariances of the measurements and of the predictions.
Accuracy