MSACRobustLateration2DSolver.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.MSACRobustEstimator;
import com.irurueta.numerical.robust.MSACRobustEstimatorListener;
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 MSAC algorithm to
* discard outliers.
*/
@SuppressWarnings("Duplicates")
public class MSACRobustLateration2DSolver 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;
/**
* Threshold to determine whether samples are inliers or not when
* testing possible estimation solutions.
*/
private double threshold = DEFAULT_THRESHOLD;
/**
* Constructor.
*/
public MSACRobustLateration2DSolver() {
super();
}
/**
* Constructor.
*
* @param listener listener to be notified of events such as when estimation
* starts, ends or its progress significantly changes.
*/
public MSACRobustLateration2DSolver(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 or their length is smaller than required (3 points).
*/
public MSACRobustLateration2DSolver(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 MSACRobustLateration2DSolver(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 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 MSACRobustLateration2DSolver(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 starts,
* 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 MSACRobustLateration2DSolver(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 of circles array
* is less than required (3 points).
*/
public MSACRobustLateration2DSolver(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 MSACRobustLateration2DSolver(
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 MSACRobustLateration2DSolver(
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 MSACRobustLateration2DSolver(
final Circle[] circles, final double[] distanceStandardDeviations,
final RobustLaterationSolverListener<Point2D> listener) {
super(circles, distanceStandardDeviations, listener);
}
/**
* Returns threshold to determine whether samples are inliers or not.
*
* @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.
*
* @param threshold threshold to be set.
* @throws IllegalArgumentException if provided value is equal or less than
* zero.
* @throws LockedException if robust estimator is locked because an
* estimation is already in progress.
*/
public void setThreshold(final double threshold) throws LockedException {
if (isLocked()) {
throw new LockedException();
}
if (threshold <= MIN_THRESHOLD) {
throw new IllegalArgumentException();
}
this.threshold = threshold;
}
/**
* 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 MSACRobustEstimator<>(new MSACRobustEstimatorListener<Point2D>() {
@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 MSACRobustLateration2DSolver.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(MSACRobustLateration2DSolver.this, iteration);
}
}
@Override
public void onEstimateProgressChange(final RobustEstimator<Point2D> estimator, final float progress) {
if (listener != null) {
listener.onSolveProgressChange(MSACRobustLateration2DSolver.this, progress);
}
}
});
try {
locked = true;
if (listener != null) {
listener.onSolveStart(this);
}
inliersData = null;
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.MSAC;
}
}