Class PROMedSRobustKnownFrameGyroscopeCalibrator
java.lang.Object
com.irurueta.navigation.inertial.calibration.gyroscope.RobustKnownFrameGyroscopeCalibrator
com.irurueta.navigation.inertial.calibration.gyroscope.PROMedSRobustKnownFrameGyroscopeCalibrator
- All Implemented Interfaces:
GyroscopeCalibrator
,GyroscopeNonLinearCalibrator
,OrderedStandardDeviationFrameBodyKinematicsGyroscopeCalibrator
,QualityScoredGyroscopeCalibrator
,UnknownBiasGyroscopeCalibrator
,UnknownBiasNonLinearGyroscopeCalibrator
,GyroscopeBiasUncertaintySource
,GyroscopeCalibrationSource
Robustly estimates gyroscope biases, cross couplings and scaling factors
along with G-dependent cross biases introduced on the gyroscope by the
specific forces sensed by the accelerometer using a PROMedS algorithm to discard
outliers.
To use this calibrator at least 7 measurements at different known frames must be provided. In other words, accelerometer and gyroscope (i.e. body kinematics) samples must be obtained at 7 different positions, orientations and velocities (although typically velocities are always zero).
Measured gyroscope angular rates is assumed to follow the model shown below:
Ωmeas = bg + (I + Mg) * Ωtrue + Gg * ftrue + wWhere: - Ωmeas is the measured gyroscope angular rates. This is a 3x1 vector. - bg is the gyroscope bias. Ideally, on a perfect gyroscope, this should be a 3x1 zero vector. - I is the 3x3 identity matrix. - Mg is the 3x3 matrix containing cross-couplings and scaling factors. Ideally, on a perfect gyroscope, this should be a 3x3 zero matrix. - Ωtrue is ground-truth gyroscope angular rates. - Gg is the G-dependent cross biases introduced by the specific forces sensed by the accelerometer. Ideally, on a perfect gyroscope, this should be a 3x3 zero matrix. - ftrue is ground-truth specific force. This is a 3x1 vector. - w is measurement noise. This is a 3x1 vector.
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Nested Class Summary
Nested classes/interfaces inherited from class com.irurueta.navigation.inertial.calibration.gyroscope.RobustKnownFrameGyroscopeCalibrator
RobustKnownFrameGyroscopeCalibrator.PreliminaryResult
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Field Summary
FieldsModifier and TypeFieldDescriptionstatic final double
Default value to be used for stop threshold.static final double
Minimum allowed stop threshold value.private double[]
Quality scores corresponding to each provided sample.private double
Threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough.Fields inherited from class com.irurueta.navigation.inertial.calibration.gyroscope.RobustKnownFrameGyroscopeCalibrator
confidence, DEFAULT_CONFIDENCE, DEFAULT_KEEP_COVARIANCE, DEFAULT_MAX_ITERATIONS, DEFAULT_PROGRESS_DELTA, DEFAULT_REFINE_PRELIMINARY_SOLUTIONS, DEFAULT_REFINE_RESULT, DEFAULT_ROBUST_METHOD, DEFAULT_USE_COMMON_Z_AXIS, DEFAULT_USE_LINEAR_CALIBRATOR, inliersData, listener, MAX_CONFIDENCE, MAX_PROGRESS_DELTA, maxIterations, measurements, MIN_CONFIDENCE, MIN_ITERATIONS, MIN_PROGRESS_DELTA, MINIMUM_MEASUREMENTS, preliminarySubsetSize, progressDelta, refineResult, running
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Constructor Summary
ConstructorsConstructorDescriptionConstructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(boolean commonAxisUsed) Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(boolean commonAxisUsed, RobustKnownFrameGyroscopeCalibratorListener listener) Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(double[] qualityScores) Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(double[] qualityScores, boolean commonAxisUsed) Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(double[] qualityScores, boolean commonAxisUsed, RobustKnownFrameGyroscopeCalibratorListener listener) Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(double[] qualityScores, RobustKnownFrameGyroscopeCalibratorListener listener) Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(double[] qualityScores, List<StandardDeviationFrameBodyKinematics> measurements) Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(double[] qualityScores, List<StandardDeviationFrameBodyKinematics> measurements, boolean commonAxisUsed) Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(double[] qualityScores, List<StandardDeviationFrameBodyKinematics> measurements, boolean commonAxisUsed, RobustKnownFrameGyroscopeCalibratorListener listener) Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(double[] qualityScores, List<StandardDeviationFrameBodyKinematics> measurements, RobustKnownFrameGyroscopeCalibratorListener listener) Constructor.Constructor.Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(List<StandardDeviationFrameBodyKinematics> measurements, boolean commonAxisUsed) Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(List<StandardDeviationFrameBodyKinematics> measurements, boolean commonAxisUsed, RobustKnownFrameGyroscopeCalibratorListener listener) Constructor.PROMedSRobustKnownFrameGyroscopeCalibrator
(List<StandardDeviationFrameBodyKinematics> measurements, RobustKnownFrameGyroscopeCalibratorListener listener) Constructor. -
Method Summary
Modifier and TypeMethodDescriptionvoid
Estimates accelerometer calibration parameters containing bias, scale factors and cross-coupling errors.com.irurueta.numerical.robust.RobustEstimatorMethod
Returns method being used for robust estimation.double[]
Returns quality scores corresponding to each provided sample.double
Returns threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough.private void
internalSetQualityScores
(double[] qualityScores) Sets quality scores corresponding to each provided sample.boolean
Indicates whether this calibrator requires quality scores for each measurement/sequence or not.boolean
isReady()
Indicates whether solver is ready to find a solution.void
setQualityScores
(double[] qualityScores) Sets quality scores corresponding to each provided sample.void
setStopThreshold
(double stopThreshold) Sets threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough.Methods inherited from class com.irurueta.navigation.inertial.calibration.gyroscope.RobustKnownFrameGyroscopeCalibrator
attemptRefine, computeError, computePreliminarySolutions, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, create, getConfidence, getEstimatedBiasAngularSpeedX, getEstimatedBiasAngularSpeedX, getEstimatedBiasAngularSpeedY, getEstimatedBiasAngularSpeedY, getEstimatedBiasAngularSpeedZ, getEstimatedBiasAngularSpeedZ, getEstimatedBiasAsTriad, getEstimatedBiasAsTriad, getEstimatedBiases, getEstimatedBiases, getEstimatedBiasesAsMatrix, getEstimatedBiasesAsMatrix, getEstimatedBiasStandardDeviation, getEstimatedBiasStandardDeviation, getEstimatedBiasStandardDeviationAverage, getEstimatedBiasStandardDeviationAverageAsAngularSpeed, getEstimatedBiasStandardDeviationAverageAsAngularSpeed, getEstimatedBiasStandardDeviationNorm, getEstimatedBiasStandardDeviationNormAsAngularSpeed, getEstimatedBiasStandardDeviationNormAsAngularSpeed, getEstimatedBiasX, getEstimatedBiasXStandardDeviation, getEstimatedBiasXStandardDeviationAsAngularSpeed, getEstimatedBiasXStandardDeviationAsAngularSpeed, getEstimatedBiasXVariance, getEstimatedBiasY, getEstimatedBiasYStandardDeviation, getEstimatedBiasYStandardDeviationAsAngularSpeed, getEstimatedBiasYStandardDeviationAsAngularSpeed, getEstimatedBiasYVariance, getEstimatedBiasZ, getEstimatedBiasZStandardDeviation, getEstimatedBiasZStandardDeviationAsAngularSpeed, getEstimatedBiasZStandardDeviationAsAngularSpeed, getEstimatedBiasZVariance, getEstimatedChiSq, getEstimatedCovariance, getEstimatedGg, getEstimatedMg, getEstimatedMse, getEstimatedMxy, getEstimatedMxz, getEstimatedMyx, getEstimatedMyz, getEstimatedMzx, getEstimatedMzy, getEstimatedSx, getEstimatedSy, getEstimatedSz, getInitialBias, getInitialBias, getInitialBiasAngularSpeedX, getInitialBiasAngularSpeedX, getInitialBiasAngularSpeedY, getInitialBiasAngularSpeedY, getInitialBiasAngularSpeedZ, getInitialBiasAngularSpeedZ, getInitialBiasAsMatrix, getInitialBiasAsMatrix, getInitialBiasAsTriad, getInitialBiasAsTriad, getInitialBiasX, getInitialBiasY, getInitialBiasZ, getInitialGg, getInitialGg, getInitialMg, getInitialMg, getInitialMxy, getInitialMxz, getInitialMyx, getInitialMyz, getInitialMzx, getInitialMzy, getInitialSx, getInitialSy, getInitialSz, getInliersData, getListener, getMaxIterations, getMeasurementOrSequenceType, getMeasurements, getMinimumRequiredMeasurementsOrSequences, getPreliminarySubsetSize, getProgressDelta, isCommonAxisUsed, isCovarianceKept, isLinearCalibratorUsed, isOrderedMeasurementsOrSequencesRequired, isPreliminarySolutionRefined, isResultRefined, isRunning, setCommonAxisUsed, setConfidence, setCovarianceKept, setInitialBias, setInitialBias, setInitialBias, setInitialBias, setInitialBias, setInitialBiasX, setInitialBiasX, setInitialBiasY, setInitialBiasY, setInitialBiasZ, setInitialBiasZ, setInitialCrossCouplingErrors, setInitialGg, setInitialMg, setInitialMxy, setInitialMxz, setInitialMyx, setInitialMyz, setInitialMzx, setInitialMzy, setInitialScalingFactors, setInitialScalingFactorsAndCrossCouplingErrors, setInitialSx, setInitialSy, setInitialSz, setLinearCalibratorUsed, setListener, setMaxIterations, setMeasurements, setPreliminarySolutionRefined, setPreliminarySubsetSize, setProgressDelta, setResultRefined
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Field Details
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DEFAULT_STOP_THRESHOLD
public static final double DEFAULT_STOP_THRESHOLDDefault value to be used for stop threshold. Stop threshold can be used to avoid keeping the algorithm unnecessarily iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the LMedS algorithm iterating too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.- See Also:
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MIN_STOP_THRESHOLD
public static final double MIN_STOP_THRESHOLDMinimum allowed stop threshold value.- See Also:
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stopThreshold
private double stopThresholdThreshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the LMedS algorithm iterating too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results. -
qualityScores
private double[] qualityScoresQuality scores corresponding to each provided sample. The larger the score value the better the quality of the sample.
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Constructor Details
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PROMedSRobustKnownFrameGyroscopeCalibrator
public PROMedSRobustKnownFrameGyroscopeCalibrator()Constructor. -
PROMedSRobustKnownFrameGyroscopeCalibrator
public PROMedSRobustKnownFrameGyroscopeCalibrator(List<StandardDeviationFrameBodyKinematics> measurements) Constructor.- Parameters:
measurements
- list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).
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PROMedSRobustKnownFrameGyroscopeCalibrator
public PROMedSRobustKnownFrameGyroscopeCalibrator(boolean commonAxisUsed) Constructor.- Parameters:
commonAxisUsed
- indicates whether z-axis is assumed to be common for accelerometer and gyroscope.
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PROMedSRobustKnownFrameGyroscopeCalibrator
public PROMedSRobustKnownFrameGyroscopeCalibrator(List<StandardDeviationFrameBodyKinematics> measurements, boolean commonAxisUsed) Constructor.- Parameters:
measurements
- list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).commonAxisUsed
- indicates whether z-axis is assumed to be common for accelerometer and gyroscope.
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PROMedSRobustKnownFrameGyroscopeCalibrator
public PROMedSRobustKnownFrameGyroscopeCalibrator(double[] qualityScores) Constructor.- Parameters:
qualityScores
- quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.- Throws:
IllegalArgumentException
- if provided quality scores length is smaller than 7 samples.
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PROMedSRobustKnownFrameGyroscopeCalibrator
public PROMedSRobustKnownFrameGyroscopeCalibrator(double[] qualityScores, List<StandardDeviationFrameBodyKinematics> measurements) Constructor.- Parameters:
qualityScores
- quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.measurements
- list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).- Throws:
IllegalArgumentException
- if provided quality scores length is smaller than 7 samples.
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PROMedSRobustKnownFrameGyroscopeCalibrator
public PROMedSRobustKnownFrameGyroscopeCalibrator(double[] qualityScores, boolean commonAxisUsed) Constructor.- Parameters:
qualityScores
- quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.commonAxisUsed
- indicates whether z-axis is assumed to be common for accelerometer and gyroscope.- Throws:
IllegalArgumentException
- if provided quality scores length is smaller than 7 samples.
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PROMedSRobustKnownFrameGyroscopeCalibrator
public PROMedSRobustKnownFrameGyroscopeCalibrator(double[] qualityScores, List<StandardDeviationFrameBodyKinematics> measurements, boolean commonAxisUsed) Constructor.- Parameters:
qualityScores
- quality scores corresponding to each provided measurement. The larger the score value the better the quality of the sample.measurements
- list of body kinematics measurements with standard deviations taken at different frames (positions, orientations and velocities).commonAxisUsed
- indicates whether z-axis is assumed to be common for accelerometer and gyroscope.- Throws:
IllegalArgumentException
- if provided quality scores length is smaller than 7 samples.
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Method Details
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getStopThreshold
public double getStopThreshold()Returns threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the LMedS algorithm to iterate too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.- Returns:
- stop threshold to stop the algorithm prematurely when a certain accuracy has been reached.
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setStopThreshold
public void setStopThreshold(double stopThreshold) throws com.irurueta.navigation.LockedException Sets threshold to be used to keep the algorithm iterating in case that best estimated threshold using median of residuals is not small enough. Once a solution is found that generates a threshold below this value, the algorithm will stop. The stop threshold can be used to prevent the LMedS algorithm to iterate too many times in cases where samples have a very similar accuracy. For instance, in cases where proportion of outliers is very small (close to 0%), and samples are very accurate (i.e. 1e-6), the algorithm would iterate for a long time trying to find the best solution when indeed there is no need to do that if a reasonable threshold has already been reached. Because of this behaviour the stop threshold can be set to a value much lower than the one typically used in RANSAC, and yet the algorithm could still produce even smaller thresholds in estimated results.- Parameters:
stopThreshold
- stop threshold to stop the algorithm prematurely when a certain accuracy has been reached.- Throws:
IllegalArgumentException
- if provided value is zero or negative.com.irurueta.navigation.LockedException
- if calibrator is currently running.
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getQualityScores
public double[] getQualityScores()Returns quality scores corresponding to each provided sample. The larger the score value the better the quality of the sample.- Specified by:
getQualityScores
in interfaceQualityScoredGyroscopeCalibrator
- Overrides:
getQualityScores
in classRobustKnownFrameGyroscopeCalibrator
- Returns:
- quality scores corresponding to each sample.
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setQualityScores
public void setQualityScores(double[] qualityScores) throws com.irurueta.navigation.LockedException Sets quality scores corresponding to each provided sample. The larger the score value the better the quality of the sample.- Specified by:
setQualityScores
in interfaceQualityScoredGyroscopeCalibrator
- Overrides:
setQualityScores
in classRobustKnownFrameGyroscopeCalibrator
- Parameters:
qualityScores
- quality scores corresponding to each sample.- Throws:
IllegalArgumentException
- if provided quality scores length is smaller than minimum required samples.com.irurueta.navigation.LockedException
- if calibrator is currently running.
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isReady
public boolean isReady()Indicates whether solver is ready to find a solution.- Specified by:
isReady
in interfaceGyroscopeCalibrator
- Overrides:
isReady
in classRobustKnownFrameGyroscopeCalibrator
- Returns:
- true if solver is ready, false otherwise.
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calibrate
public void calibrate() throws com.irurueta.navigation.LockedException, com.irurueta.navigation.NotReadyException, CalibrationExceptionEstimates accelerometer calibration parameters containing bias, scale factors and cross-coupling errors.- Throws:
com.irurueta.navigation.LockedException
- if calibrator is currently running.com.irurueta.navigation.NotReadyException
- if calibrator is not ready.CalibrationException
- if estimation fails for numerical reasons.
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getMethod
public com.irurueta.numerical.robust.RobustEstimatorMethod getMethod()Returns method being used for robust estimation.- Specified by:
getMethod
in classRobustKnownFrameGyroscopeCalibrator
- Returns:
- method being used for robust estimation.
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isQualityScoresRequired
public boolean isQualityScoresRequired()Indicates whether this calibrator requires quality scores for each measurement/sequence or not.- Returns:
- true if quality scores are required, false otherwise.
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internalSetQualityScores
private void internalSetQualityScores(double[] qualityScores) Sets quality scores corresponding to each provided sample. This method is used internally and does not check whether instance is locked or not.- Parameters:
qualityScores
- quality scores to be set.- Throws:
IllegalArgumentException
- if provided quality scores length is smaller than 3 samples.
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