State estimation for aerial vehicles using multi-sensor fusion
First Claim
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1. A system for estimating the state of an aerial vehicle comprising:
- one or more relative sensors, including at least an inertial measurement unit and a visual odometry unit;
one or more absolute sensors; and
a processor, running software for performing the functions of;
keeping a current state and current state covariance, the current state including at least a current position, a current orientation, a current velocity, a delayed position and a delayed orientation, the delayed position and delayed orientation being based on visual odometry from a previous current state;
predicting an update of the current state and an update of the current state covariance based on an integration of a reading from the inertial measurement unit;
receiving visual odometry, updating the delayed position and orientation with the current position and orientation, updating the current position and orientation with the visual odometry;
receiving state information from an absolute sensor, updating the current state with the state information and covariance from the absolute sensor;
recalculating the covariance of the current state to give readings from the relative and absolute sensors a weight in the estimated state of the vehicle; and
repeating the functions performed by the software.
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Abstract
A state estimation system that utilizes long-range stereo visual odometry that can degrade to a monocular system at high-altitude, and integrates GPS, Barometer and IMU measurements. The system has two main parts: An EKF that is loosely fused and a long-range visual odometry part. For visual odometry, the system takes the EKF information for robust camera pose tracking, and the visual odometry outputs will be the measurement for EKF state update.
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Citations
18 Claims
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1. A system for estimating the state of an aerial vehicle comprising:
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one or more relative sensors, including at least an inertial measurement unit and a visual odometry unit; one or more absolute sensors; and a processor, running software for performing the functions of; keeping a current state and current state covariance, the current state including at least a current position, a current orientation, a current velocity, a delayed position and a delayed orientation, the delayed position and delayed orientation being based on visual odometry from a previous current state; predicting an update of the current state and an update of the current state covariance based on an integration of a reading from the inertial measurement unit; receiving visual odometry, updating the delayed position and orientation with the current position and orientation, updating the current position and orientation with the visual odometry; receiving state information from an absolute sensor, updating the current state with the state information and covariance from the absolute sensor; recalculating the covariance of the current state to give readings from the relative and absolute sensors a weight in the estimated state of the vehicle; and repeating the functions performed by the software. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method for estimating the state of an aerial vehicle comprising:
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keeping a current state and current state covariance, the current state including at least a current position, a current orientation, a current velocity, a delayed position and a delayed orientation, the delayed position and delayed orientation being based on visual odometry from a previous current state; predicting an update of the current state and an update of the current state covariance based on an integration of a reading from an inertial measurement unit; receiving visual odometry from a visual odometry unit, updating the delayed position and orientation with the current position and orientation, updating the current position and orientation with the visual odometry and recalculating the covariance of the current state; receiving state information from an absolute sensor, updating the current state and with the state information and covariance from the absolute sensor and recalculating the covariance of the current state; and repeating the functions performed by the software. - View Dependent Claims (13, 14, 15, 16, 17, 18)
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Specification