SimpleSensorNoise.cpp

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// kate: replace-tabs off; indent-width 4; indent-mode normal
// vim: ts=4:sw=4:noexpandtab
/*

Copyright (c) 2010--2018,
François Pomerleau and Stephane Magnenat, ASL, ETHZ, Switzerland
You can contact the authors at <f dot pomerleau at gmail dot com> and
<stephane at magnenat dot net>

All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
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      notice, this list of conditions and the following disclaimer.
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    * Neither the name of the <organization> nor the
      names of its contributors may be used to endorse or promote products
      derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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*/
#include "SimpleSensorNoise.h"

#include "PointMatcherPrivate.h"

#include <string>
#include <vector>

#include <boost/format.hpp>

// SimpleSensorNoiseDataPointsFilter
// Constructor
template<typename T>
SimpleSensorNoiseDataPointsFilter<T>::SimpleSensorNoiseDataPointsFilter(const Parameters& params):
        PointMatcher<T>::DataPointsFilter("SimpleSensorNoiseDataPointsFilter",
        SimpleSensorNoiseDataPointsFilter::availableParameters(), params),
        sensorType(Parametrizable::get<unsigned>("sensorType")),
        gain(Parametrizable::get<T>("gain"))
{
        std::vector<std::string> sensorNames = {"Sick LMS-1xx",
                                                                                        "Hokuyo URG-04LX",
                                                                                        "Hokuyo UTM-30LX",
                                                                                        "Kinect / Xtion","Sick Tim3xx"};
        if (sensorType >= sensorNames.size())
        {
                throw InvalidParameter(
                        (boost::format("SimpleSensorNoiseDataPointsFilter: Error, sensorType id %1% does not exist.") % sensorType).str());
        }

        LOG_INFO_STREAM("SimpleSensorNoiseDataPointsFilter - using sensor noise model: " << sensorNames[sensorType]);
}


// SimpleSensorNoiseDataPointsFilter
// Compute
template<typename T>
typename PointMatcher<T>::DataPoints 
SimpleSensorNoiseDataPointsFilter<T>::filter(const DataPoints& input)
{
        DataPoints output(input);
        inPlaceFilter(output);
        return output;
}

// In-place filter
template<typename T>
void SimpleSensorNoiseDataPointsFilter<T>::inPlaceFilter(DataPoints& cloud)
{
        cloud.allocateDescriptor("simpleSensorNoise", 1);
        BOOST_AUTO(noise, cloud.getDescriptorViewByName("simpleSensorNoise"));

        switch(sensorType)
        {
        case 0: // Sick LMS-1xx
        {
                noise = computeLaserNoise(0.012, 0.0068, 0.0008, cloud.features);
                break;
        }
        case 1: // Hokuyo URG-04LX
        {
                noise = computeLaserNoise(0.028, 0.0013, 0.0001, cloud.features);
                break;
        }
        case 2: // Hokuyo UTM-30LX
        {
                noise = computeLaserNoise(0.018, 0.0006, 0.0015, cloud.features);
                break;
        }
        case 3: // Kinect / Xtion
        {
                const int dim = cloud.features.rows();
                const Matrix squaredValues(cloud.features.topRows(dim-1).colwise().norm().array().square());
                noise = squaredValues*(0.5*0.00285);
                break;
        }
  case 4: // Sick Tim3xx
  {
    noise = computeLaserNoise(0.004, 0.0053, -0.0092, cloud.features);
    break;
  }
        default:
                throw InvalidParameter(
                        (boost::format("SimpleSensorNoiseDataPointsFilter: Error, cannot compute noise for sensorType id %1% .") % sensorType).str());
        }

}

template<typename T>
typename PointMatcher<T>::Matrix 
SimpleSensorNoiseDataPointsFilter<T>::computeLaserNoise(
        const T minRadius, const T beamAngle, const T beamConst, const Matrix& features)
{
        typedef typename Eigen::Array<T, 2, Eigen::Dynamic> Array2rows;

        const int nbPoints = features.cols();
        const int dim = features.rows();

        Array2rows evalNoise = Array2rows::Constant(2, nbPoints, minRadius);
        evalNoise.row(0) =  beamAngle * features.topRows(dim-1).colwise().norm();
        evalNoise.row(0) += beamConst;

        return evalNoise.colwise().maxCoeff();
}


template struct SimpleSensorNoiseDataPointsFilter<float>;
template struct SimpleSensorNoiseDataPointsFilter<double>;