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The observer structure consists of four parts; (a) attitude and gyro bias estimation, (b) time-delayed translational motion observer estimating position and linear velocity, (c) input delays for inertial and magnetometer measurements, and (d) a faster than real-time simulator.
Several approaches to estimating position and orientation are described at the end of the materials and methods section.
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Positive feedback is generated when users reject the estimated position and suggest a location based on their knowledge.
In Monocular Simultaneous Localization and Mapping (SLAM), EKF is used to estimate position and motion information.
In order to estimate position and velocity error of the spacecraft and reduce the impact of the system noise on navigation precision, an adaptive divided difference filter (ADDF) is applied.
First, we calculate the distance (error) squared between the estimated position and the true position.
Then temporal trajectories are built based on the estimated position and velocity.
Therefore, the error between the estimated position and actual position should be small and within a certain range.
We confirmed the error of the estimated position and the accuracy of repeatability of MoMo3 in the following experiment.
Therefore a tiny change of the observation would result in large variation on the camera's estimated position and orientation.
The localization is considered successful if the distance difference between the estimated position and the real position of the sensor is less than a threshold.
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