PROSACRobustLateration2DSolver.java
/*
* Copyright (C) 2018 Alberto Irurueta Carro (alberto@irurueta.com)
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.irurueta.navigation.lateration;
import com.irurueta.geometry.Circle;
import com.irurueta.geometry.Point2D;
import com.irurueta.navigation.LockedException;
import com.irurueta.navigation.NotReadyException;
import com.irurueta.numerical.robust.PROSACRobustEstimator;
import com.irurueta.numerical.robust.PROSACRobustEstimatorListener;
import com.irurueta.numerical.robust.RobustEstimator;
import com.irurueta.numerical.robust.RobustEstimatorException;
import com.irurueta.numerical.robust.RobustEstimatorMethod;
import java.util.List;
/**
* Robustly solves the lateration problem by finding the best pairs of 2D
* positions and distances among the provided ones using PROSAC algorithm to
* discard outliers.
*/
@SuppressWarnings("Duplicates")
public class PROSACRobustLateration2DSolver extends RobustLateration2DSolver {
/**
* Constant defining default threshold to determine whether samples are inliers or not.
*/
public static final double DEFAULT_THRESHOLD = 1e-2;
/**
* Minimum value that can be set as threshold.
* Threshold must be strictly greater than 0.0.
*/
public static final double MIN_THRESHOLD = 0.0;
/**
* Indicates that by default inliers will only be computed but not kept.
*/
public static final boolean DEFAULT_COMPUTE_AND_KEEP_INLIERS = false;
/**
* Indicates that by default residuals will only be computed but not kept.
*/
public static final boolean DEFAULT_COMPUTE_AND_KEEP_RESIDUALS = false;
/**
* Threshold to determine whether samples are inliers or not when testing possible solutions.
* The threshold refers to the amount of error on distance between estimated position and
* distances provided for each sample.
*/
private double threshold = DEFAULT_THRESHOLD;
/**
* Indicates whether inliers must be computed and kept.
*/
private boolean computeAndKeepInliers = DEFAULT_COMPUTE_AND_KEEP_INLIERS;
/**
* Indicates whether residuals must be computed and kept.
*/
private boolean computeAndKeepResiduals = DEFAULT_COMPUTE_AND_KEEP_RESIDUALS;
/**
* Quality scores corresponding to each provided sample.
* The larger the score value the better the quality of the sample.
*/
private double[] qualityScores;
/**
* Constructor.
*/
public PROSACRobustLateration2DSolver() {
super();
}
/**
* Constructor.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
*/
public PROSACRobustLateration2DSolver(final RobustLaterationSolverListener<Point2D> listener) {
super(listener);
}
/**
* Constructor.
*
* @param positions known positions of static nodes.
* @param distances euclidean distances from static nodes to mobile node to be
* estimated.
* @throws IllegalArgumentException if either positions or distances are null,
* don't have the same length of their length is smaller than required (3 points).
*/
public PROSACRobustLateration2DSolver(final Point2D[] positions, final double[] distances) {
super(positions, distances);
}
/**
* Constructor.
*
* @param positions known positions of static nodes.
* @param distances euclidean distances from static nodes to mobile node to be
* estimated.
* @param distanceStandardDeviations standard deviations of provided measured distances.
* @throws IllegalArgumentException if either positions or distances are null,
* don't have the same length or their length is smaller than required (3 points).
*/
public PROSACRobustLateration2DSolver(final Point2D[] positions, final double[] distances,
final double[] distanceStandardDeviations) {
super(positions, distances, distanceStandardDeviations);
}
/**
* Constructor.
*
* @param positions known positions of static nodes.
* @param distances euclidean distances from static nodes to mobile node.
* @param distanceStandardDeviations standard deviations of provided measured distances.
* @param listener listener to be notified of events such as when estimation stats,
* ends or its progress significantly changes.
* @throws IllegalArgumentException if either positions, distances or
* standard deviations are null, don't have the same length or their length is
* smaller than required (3 points).
*/
public PROSACRobustLateration2DSolver(
final Point2D[] positions, final double[] distances, final double[] distanceStandardDeviations,
final RobustLaterationSolverListener<Point2D> listener) {
super(positions, distances, distanceStandardDeviations, listener);
}
/**
* Constructor.
*
* @param positions known positions of static nodes.
* @param distances euclidean distances from static nodes to mobile node.
* @param listener listener to be notified of events such as when estimation stats,
* ends or its progress significantly changes.
* @throws IllegalArgumentException if either positions or distances are null,
* don't have the same length or their length is smaller than required (3 points).
*/
public PROSACRobustLateration2DSolver(
final Point2D[] positions, final double[] distances,
final RobustLaterationSolverListener<Point2D> listener) {
super(positions, distances, listener);
}
/**
* Constructor.
*
* @param circles circles defining positions and distances.
* @throws IllegalArgumentException if circles is null or if length or circles array
* is less than required (3 points).
*/
public PROSACRobustLateration2DSolver(final Circle[] circles) {
super(circles);
}
/**
* Constructor.
*
* @param circles circles defining positions and distances.
* @param distanceStandardDeviations standard deviations of provided measured distances.
* @throws IllegalArgumentException if circles is null, length of circles array is less
* than required (3 points) or don't have the same length.
*/
public PROSACRobustLateration2DSolver(final Circle[] circles, final double[] distanceStandardDeviations) {
super(circles, distanceStandardDeviations);
}
/**
* Constructor.
*
* @param circles circles defining positions and distances.
* @param listener listener to be notified of events such as when estimation starts,
* ends or its progress significantly changes.
* @throws IllegalArgumentException if circles is null or if length of circles array
* is less than required (3 points).
*/
public PROSACRobustLateration2DSolver(
final Circle[] circles, final RobustLaterationSolverListener<Point2D> listener) {
super(circles, listener);
}
/**
* Constructor.
*
* @param circles circles defining positions and distances.
* @param distanceStandardDeviations standard deviations of provided measured distances.
* @param listener listener to be notified of events such as when estimation starts,
* ends or its progress significantly changes.
* @throws IllegalArgumentException if circles is null, length of circles array is less
* than required (3 points) or don't have the same length.
*/
public PROSACRobustLateration2DSolver(
final Circle[] circles, final double[] distanceStandardDeviations,
final RobustLaterationSolverListener<Point2D> listener) {
super(circles, distanceStandardDeviations, listener);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided
* sample. The larger the score value the better
* the quality of the sample.
* @throws IllegalArgumentException if quality scores is null, length
* of quality scores is less than required minimum (3 samples).
*/
public PROSACRobustLateration2DSolver(final double[] qualityScores) {
super();
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided
* sample. The larger the score value the better
* the quality of the sample.
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
* @throws IllegalArgumentException if quality scores is null, length
* of quality scores is less than required minimum (3 samples).
*/
public PROSACRobustLateration2DSolver(
final double[] qualityScores, final RobustLaterationSolverListener<Point2D> listener) {
super(listener);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided
* sample. The larger the score value the better
* the quality of the sample.
* @param positions known positions of static nodes.
* @param distances euclidean distances from static nodes to mobile node to be
* estimated.
* @throws IllegalArgumentException if either positions, distances or quality
* scores are null, don't have the same length of their length is smaller
* than required (3 points).
*/
public PROSACRobustLateration2DSolver(
final double[] qualityScores, final Point2D[] positions, final double[] distances) {
super(positions, distances);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided
* sample. The larger the score value the better
* the quality of the sample.
* @param positions known positions of static nodes.
* @param distances euclidean distances from static nodes to mobile node to be
* estimated.
* @param distanceStandardDeviations standard deviations of provided measured distances.
* @throws IllegalArgumentException if either positions, distances, quality scores or
* standard deviations are null, don't have the same length or their length is
* smaller than required (3 points).
*/
public PROSACRobustLateration2DSolver(
final double[] qualityScores, final Point2D[] positions, final double[] distances,
final double[] distanceStandardDeviations) {
super(positions, distances, distanceStandardDeviations);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided
* sample. The larger the score value the better
* the quality of the sample.
* @param positions known positions of static nodes.
* @param distances euclidean distances from static nodes to mobile node.
* @param distanceStandardDeviations standard deviations of provided measured distances.
* @param listener listener to be notified of events such as when estimation starts,
* ends or its progress significantly changes.
* @throws IllegalArgumentException if either positions, distances or
* standard deviations are null, don't have the same length or their length is
* smaller than required (3 points).
*/
public PROSACRobustLateration2DSolver(
final double[] qualityScores, final Point2D[] positions, final double[] distances,
final double[] distanceStandardDeviations, final RobustLaterationSolverListener<Point2D> listener) {
super(positions, distances, distanceStandardDeviations, listener);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided
* sample. The larger the score value the better
* the quality of the sample.
* @param positions known positions of static nodes.
* @param distances euclidean distances from static nodes to mobile node.
* @param listener listener to be notified of events such as when
* estimation starts, ends or its progress significantly changes.
* @throws IllegalArgumentException if either positions, distances,
* quality scores or standard deviations are null, don't have the same
* length or their length is smaller than required (3 points).
*/
public PROSACRobustLateration2DSolver(
final double[] qualityScores, final Point2D[] positions, final double[] distances,
final RobustLaterationSolverListener<Point2D> listener) {
super(positions, distances, listener);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided
* sample. The larger the score value the better
* the quality of the sample.
* @param circles circles defining positions and distances.
* @throws IllegalArgumentException if either circles or quality scores
* are null don't have the same length or their length is less than
* required (3 points).
*/
public PROSACRobustLateration2DSolver(final double[] qualityScores, final Circle[] circles) {
super(circles);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided
* sample. The larger the score value the better
* the quality of the sample.
* @param circles circles defining positions and distances.
* @param distanceStandardDeviations standard deviations of provided measured distances.
* @throws IllegalArgumentException if either circles, quality scores or
* standard deviations are null, don't have the same length or their
* length is less than required (3 points).
*/
public PROSACRobustLateration2DSolver(
final double[] qualityScores, final Circle[] circles, final double[] distanceStandardDeviations) {
super(circles, distanceStandardDeviations);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided
* sample. The larger the score value the better
* the quality of the sample.
* @param circles circles defining positions and distances.
* @param listener listener to be notified of events such as when estimation starts,
* ends or its progress significantly changes.
* @throws IllegalArgumentException if either circles or quality scores
* are null, don't have the same length or their length is less than
* required (3 points).
*/
public PROSACRobustLateration2DSolver(
final double[] qualityScores, final Circle[] circles,
final RobustLaterationSolverListener<Point2D> listener) {
super(circles, listener);
internalSetQualityScores(qualityScores);
}
/**
* Constructor.
*
* @param qualityScores quality scores corresponding to each provided
* sample. The larger the score value the better
* the quality of the sample.
* @param circles circles defining positions and distances.
* @param distanceStandardDeviations standard deviations of provided measured distances.
* @param listener listener to be notified of events such as when estimation starts,
* ends or its progress significantly changes.
* @throws IllegalArgumentException if either circles, quality scores
* or standard deviations are null, don't have the same length or their
* length is less than required (3 points).
*/
public PROSACRobustLateration2DSolver(
final double[] qualityScores, final Circle[] circles, final double[] distanceStandardDeviations,
final RobustLaterationSolverListener<Point2D> listener) {
super(circles, distanceStandardDeviations, listener);
internalSetQualityScores(qualityScores);
}
/**
* Gets threshold to determine whether samples are inliers or not when testing possible solutions.
* The threshold refers to the amount of error on distance between estimated position and distances
* provided for each sample.
*
* @return threshold to determine whether samples are inliers or not.
*/
public double getThreshold() {
return threshold;
}
/**
* Sets threshold to determine whether samples are inliers or not when testing possible solutions.
* The threshold refers to the amount of error on distance between estimated position and distances
* provided for each sample.
*
* @param threshold threshold to determine whether samples are inliers or not.
* @throws IllegalArgumentException if provided value is equal or less than zero.
* @throws LockedException if this solver is locked.
*/
public void setThreshold(final double threshold) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
if (threshold <= MIN_THRESHOLD) {
throw new IllegalArgumentException();
}
this.threshold = threshold;
}
/**
* Returns quality scores corresponding to each pair of
* positions and distances (i.e. sample).
* The larger the score value the better the quality of the sample.
*
* @return quality scores corresponding to each sample.
*/
@Override
public double[] getQualityScores() {
return qualityScores;
}
/**
* Sets quality scores corresponding to each pair of positions and
* distances (i.e. sample).
* The larger the score value the better the quality of the sample.
*
* @param qualityScores quality scores corresponding to each pair of
* matched points.
* @throws IllegalArgumentException if provided quality scores length
* is smaller than minimum required samples.
* @throws LockedException if robust solver is locked because an
* estimation is already in progress.
*/
@Override
public void setQualityScores(final double[] qualityScores) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
internalSetQualityScores(qualityScores);
}
/**
* Indicates whether solver is ready to find a solution.
*
* @return true if solver is ready, false otherwise.
*/
@Override
public boolean isReady() {
return super.isReady() && qualityScores != null && qualityScores.length == distances.length;
}
/**
* Indicates whether inliers must be computed and kept.
*
* @return true if inliers must be computed and kept, false if inliers
* only need to be computed but not kept.
*/
public boolean isComputeAndKeepInliersEnabled() {
return computeAndKeepInliers;
}
/**
* Specifies whether inliers must be computed and kept.
*
* @param computeAndKeepInliers true if inliers must be computed and kept,
* false if inliers only need to be computed but not kept.
* @throws LockedException if this solver is locked.
*/
public void setComputeAndKeepInliersEnabled(final boolean computeAndKeepInliers) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
this.computeAndKeepInliers = computeAndKeepInliers;
}
/**
* Indicates whether residuals must be computed and kept.
*
* @return true if residuals must be computed and kept, false if residuals
* only need to be computed but not kept.
*/
public boolean isComputeAndKeepResiduals() {
return computeAndKeepResiduals;
}
/**
* Specifies whether residuals must be computed and kept.
*
* @param computeAndKeepResiduals true if residuals must be computed and kept,
* false if residuals only need to be computed but not kept.
* @throws LockedException if this solver is locked.
*/
public void setComputeAndKeepResidualsEnabled(final boolean computeAndKeepResiduals) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
this.computeAndKeepResiduals = computeAndKeepResiduals;
}
/**
* Solves the lateration problem.
*
* @return estimated position.
* @throws LockedException if instance is busy solving the lateration problem.
* @throws NotReadyException is solver is not ready.
* @throws RobustEstimatorException if estimation fails for any reason
* (i.e. numerical instability, no solution available, etc).
*/
@Override
public Point2D solve() throws LockedException, NotReadyException, RobustEstimatorException {
if (isLocked()) {
throw new LockedException();
}
if (!isReady()) {
throw new NotReadyException();
}
final var innerEstimator = new PROSACRobustEstimator<>(new PROSACRobustEstimatorListener<Point2D>() {
@Override
public double[] getQualityScores() {
return qualityScores;
}
@Override
public double getThreshold() {
return threshold;
}
@Override
public int getTotalSamples() {
return distances.length;
}
@Override
public int getSubsetSize() {
return preliminarySubsetSize;
}
@Override
public void estimatePreliminarSolutions(final int[] samplesIndices, final List<Point2D> solutions) {
solvePreliminarySolutions(samplesIndices, solutions);
}
@Override
public double computeResidual(final Point2D currentEstimation, final int i) {
return Math.abs(currentEstimation.distanceTo(positions[i]) - distances[i]);
}
@Override
public boolean isReady() {
return PROSACRobustLateration2DSolver.this.isReady();
}
@Override
public void onEstimateStart(final RobustEstimator<Point2D> estimator) {
// no action needed
}
@Override
public void onEstimateEnd(final RobustEstimator<Point2D> estimator) {
// no action needed
}
@Override
public void onEstimateNextIteration(final RobustEstimator<Point2D> estimator, final int iteration) {
if (listener != null) {
listener.onSolveNextIteration(PROSACRobustLateration2DSolver.this, iteration);
}
}
@Override
public void onEstimateProgressChange(final RobustEstimator<Point2D> estimator, final float progress) {
if (listener != null) {
listener.onSolveProgressChange(PROSACRobustLateration2DSolver.this, progress);
}
}
});
try {
locked = true;
if (listener != null) {
listener.onSolveStart(this);
}
inliersData = null;
innerEstimator.setComputeAndKeepInliersEnabled(computeAndKeepInliers || refineResult);
innerEstimator.setComputeAndKeepResidualsEnabled(computeAndKeepResiduals || refineResult);
innerEstimator.setConfidence(confidence);
innerEstimator.setMaxIterations(maxIterations);
innerEstimator.setProgressDelta(progressDelta);
var result = innerEstimator.estimate();
inliersData = innerEstimator.getInliersData();
result = attemptRefine(result);
if (listener != null) {
listener.onSolveEnd(this);
}
return result;
} catch (final com.irurueta.numerical.LockedException e) {
throw new LockedException(e);
} catch (final com.irurueta.numerical.NotReadyException e) {
throw new NotReadyException(e);
} finally {
locked = false;
}
}
/**
* Returns method being used for robust estimation.
*
* @return method being used for robust estimation.
*/
@Override
public RobustEstimatorMethod getMethod() {
return RobustEstimatorMethod.PROSAC;
}
/**
* Sets quality scores corresponding to each provided sample.
* This method is used internally and does not check whether instance is
* locked or not.
*
* @param qualityScores quality scores to be set.
* @throws IllegalArgumentException if provided quality scores length
* is smaller than 3 samples.
*/
private void internalSetQualityScores(final double[] qualityScores) {
if (qualityScores == null || qualityScores.length < getMinRequiredPositionsAndDistances()) {
throw new IllegalArgumentException();
}
this.qualityScores = qualityScores;
}
}