ICP.cpp

Go to the documentation of this file.

// kate: replace-tabs off; indent-width 4; indent-mode normal
// vim: ts=4:sw=4:noexpandtab
/*
 
Copyright (c) 2010--2012,
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:
    * Redistributions of source code must retain the above copyright
      notice, this list of conditions and the following disclaimer.
    * Redistributions in binary form must reproduce the above copyright
      notice, this list of conditions and the following disclaimer in the
      documentation and/or other materials provided with the distribution.
    * 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
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL ETH-ASL BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
*/
 
#include "PointMatcher.h"
#include "PointMatcherPrivate.h"
#include "Timer.h"
 
#include "LoggerImpl.h"
#include "TransformationsImpl.h"
#include "DataPointsFiltersImpl.h"
#include "MatchersImpl.h"
#include "OutlierFiltersImpl.h"
#include "ErrorMinimizersImpl.h"
#include "TransformationCheckersImpl.h"
#include "InspectorsImpl.h"
 
#include <yaml-cpp/yaml.h>
 
using namespace std;
using namespace PointMatcherSupport;
 
InvalidModuleType::InvalidModuleType(const std::string& reason):
        runtime_error(reason)
{}
 
template<typename T>
PointMatcher<T>::ICPChainBase::ICPChainBase():
        prefilteredReadingPtsCount(0),
        prefilteredReferencePtsCount(0),
        maxNumIterationsReached(false)
{}
 
template<typename T>
PointMatcher<T>::ICPChainBase::~ICPChainBase()
{
}
 
template<typename T>
void PointMatcher<T>::ICPChainBase::cleanup()
{
        transformations.clear();
        readingDataPointsFilters.clear();
        readingStepDataPointsFilters.clear();
        referenceDataPointsFilters.clear();
        matcher.reset();
        outlierFilters.clear();
        errorMinimizer.reset();
        transformationCheckers.clear();
        inspector.reset();
}
 
template<typename T>
void PointMatcher<T>::ICPChainBase::loadAdditionalYAMLContent(YAML::Node& doc)
{
}
 
template<typename T>
void PointMatcher<T>::ICPChainBase::setDefault()
{
        this->cleanup();
        
        this->transformations.push_back(std::make_shared<typename TransformationsImpl<T>::RigidTransformation>());
        this->readingDataPointsFilters.push_back(std::make_shared<typename DataPointsFiltersImpl<T>::RandomSamplingDataPointsFilter>());
        this->referenceDataPointsFilters.push_back(std::make_shared<typename DataPointsFiltersImpl<T>::SamplingSurfaceNormalDataPointsFilter>());
        this->outlierFilters.push_back(std::make_shared<typename OutlierFiltersImpl<T>::TrimmedDistOutlierFilter>());
        this->matcher = std::make_shared<typename MatchersImpl<T>::KDTreeMatcher>();
        this->errorMinimizer = std::make_shared<PointToPlaneErrorMinimizer<T> >();
        this->transformationCheckers.push_back(std::make_shared<typename TransformationCheckersImpl<T>::CounterTransformationChecker>());
        this->transformationCheckers.push_back(std::make_shared<typename TransformationCheckersImpl<T>::DifferentialTransformationChecker>());
        this->inspector = std::make_shared<typename InspectorsImpl<T>::NullInspector>();
}
 
template<typename T>
void PointMatcher<T>::ICPChainBase::loadFromYaml(std::istream& in)
{
        this->cleanup();
 
        YAML::Node doc = YAML::Load(in);
        typedef set<string> StringSet;
        StringSet usedModuleTypes;
        
        // Fix for issue #6: compilation on gcc 4.4.4
        //PointMatcher<T> pm;
        const PointMatcher & pm = PointMatcher::get();
 
        {
                // NOTE: The logger needs to be initialize first to allow ouput from other contructors
                boost::mutex::scoped_lock lock(loggerMutex);
                usedModuleTypes.insert(createModuleFromRegistrar("logger", doc, pm.REG(Logger), logger));
        }
        usedModuleTypes.insert(createModulesFromRegistrar("readingDataPointsFilters", doc, pm.REG(DataPointsFilter), readingDataPointsFilters));
        usedModuleTypes.insert(createModulesFromRegistrar("readingStepDataPointsFilters", doc, pm.REG(DataPointsFilter), readingStepDataPointsFilters));
        usedModuleTypes.insert(createModulesFromRegistrar("referenceDataPointsFilters", doc, pm.REG(DataPointsFilter), referenceDataPointsFilters));
        //usedModuleTypes.insert(createModulesFromRegistrar("transformations", doc, pm.REG(Transformation), transformations));
        usedModuleTypes.insert(createModuleFromRegistrar("matcher", doc, pm.REG(Matcher), matcher));
        usedModuleTypes.insert(createModulesFromRegistrar("outlierFilters", doc, pm.REG(OutlierFilter), outlierFilters));
        usedModuleTypes.insert(createModuleFromRegistrar("errorMinimizer", doc, pm.REG(ErrorMinimizer), errorMinimizer));
 
        // See if to use a rigid transformation
        if (nodeVal("errorMinimizer", doc) != "PointToPointSimilarityErrorMinimizer")
                this->transformations.push_back(std::make_shared<typename TransformationsImpl<T>::RigidTransformation>());
        else
                this->transformations.push_back(std::make_shared<typename TransformationsImpl<T>::SimilarityTransformation>());
        
        usedModuleTypes.insert(createModulesFromRegistrar("transformationCheckers", doc, pm.REG(TransformationChecker), transformationCheckers));
        usedModuleTypes.insert(createModuleFromRegistrar("inspector", doc, pm.REG(Inspector),inspector));
        
        
        // FIXME: this line cause segfault when there is an error in the yaml file...
        //loadAdditionalYAMLContent(doc);
        
        // check YAML entries that do not correspend to any module
        for(YAML::const_iterator moduleTypeIt = doc.begin(); moduleTypeIt != doc.end(); ++moduleTypeIt)
        {
                std::string moduleType = moduleTypeIt->first.as<std::string>();
 
                if (usedModuleTypes.find(moduleType) == usedModuleTypes.end())
                        throw InvalidModuleType(
                                (boost::format("Module type %1% does not exist") % moduleType).str()
                        );
        }
}
 
template<typename T>
unsigned PointMatcher<T>::ICPChainBase::getPrefilteredReadingPtsCount() const
{
        return prefilteredReadingPtsCount;
}
 
template<typename T>
unsigned PointMatcher<T>::ICPChainBase::getPrefilteredReferencePtsCount() const
{
        return prefilteredReferencePtsCount;
}
 
template<typename T>
bool PointMatcher<T>::ICPChainBase::getMaxNumIterationsReached() const
{
        return maxNumIterationsReached;
}
 
template<typename T>
template<typename R>
const std::string& PointMatcher<T>::ICPChainBase::createModulesFromRegistrar(const std::string& regName, const YAML::Node& doc, const R& registrar, std::vector<std::shared_ptr<typename R::TargetType> >& modules)
{
        const YAML::Node reg = doc[regName];
 
        if (reg)
        {
                //cout << regName << endl;
                for(YAML::const_iterator moduleIt = reg.begin(); moduleIt != reg.end(); ++moduleIt)
                {
                        const YAML::Node& module(*moduleIt);
                        modules.push_back(registrar.createFromYAML(module));
                }
        }
 
        return regName;
}
 
template<typename T>
template<typename R>
const std::string& PointMatcher<T>::ICPChainBase::createModuleFromRegistrar(const std::string& regName, const YAML::Node& doc, const R& registrar, std::shared_ptr<typename R::TargetType>& module)
{
        const YAML::Node reg = doc[regName];
 
        if (reg)
        {
                //cout << regName << endl;
                module = registrar.createFromYAML(reg);
        }
        else
                module.reset();
 
        return regName;
}
 
template<typename T>
std::string PointMatcher<T>::ICPChainBase::nodeVal(const std::string& regName, const YAML::Node& doc)
{
        const YAML::Node reg = doc[regName];
 
        if (reg)
        {
                std::string name;
                Parametrizable::Parameters params;
                PointMatcherSupport::getNameParamsFromYAML(reg, name, params);
 
                return name;
        }
 
        return "";
}
 
template struct PointMatcher<float>::ICPChainBase;
template struct PointMatcher<double>::ICPChainBase;
 
 
template<typename T>
typename PointMatcher<T>::TransformationParameters PointMatcher<T>::ICP::operator ()(
        const DataPoints& readingIn,
        const DataPoints& referenceIn)
{
        const int dim = readingIn.features.rows();
        const TransformationParameters identity = TransformationParameters::Identity(dim, dim);
        return this->compute(readingIn, referenceIn, identity);
}
 
template<typename T>
typename PointMatcher<T>::TransformationParameters PointMatcher<T>::ICP::operator ()(
        const DataPoints& readingIn,
        const DataPoints& referenceIn,
        const TransformationParameters& initialTransformationParameters)
{
        return this->compute(readingIn, referenceIn, initialTransformationParameters);
}
 
template<typename T>
typename PointMatcher<T>::TransformationParameters PointMatcher<T>::ICP::compute(
        const DataPoints& readingIn,
        const DataPoints& referenceIn,
        const TransformationParameters& T_refIn_dataIn)
{
        // Ensuring minimum definition of components
        if (!this->matcher)
                throw runtime_error("You must setup a matcher before running ICP");
        if (!this->errorMinimizer)
                throw runtime_error("You must setup an error minimizer before running ICP");
        if (!this->inspector)
                throw runtime_error("You must setup an inspector before running ICP");
        
        this->inspector->init();
        
        timer t; // Print how long take the algo
        const int dim(referenceIn.features.rows());
        
        // Apply reference filters
        // reference is express in frame <refIn>
        DataPoints reference(referenceIn);
        this->referenceDataPointsFilters.init();
        this->referenceDataPointsFilters.apply(reference);
        
        // Create intermediate frame at the center of mass of reference pts cloud
        //  this help to solve for rotations
        const int nbPtsReference = reference.features.cols();
        const Vector meanReference = reference.features.rowwise().sum() / nbPtsReference;
        TransformationParameters T_refIn_refMean(Matrix::Identity(dim, dim));
        T_refIn_refMean.block(0,dim-1, dim-1, 1) = meanReference.head(dim-1);
        
        // Reajust reference position: 
        // from here reference is express in frame <refMean>
        // Shortcut to do T_refIn_refMean.inverse() * reference
        reference.features.topRows(dim-1).colwise() -= meanReference.head(dim-1);
        
        // Init matcher with reference points center on its mean
        this->matcher->init(reference);
        
        // statistics on last step
        this->inspector->addStat("ReferencePreprocessingDuration", t.elapsed());
        this->inspector->addStat("ReferenceInPointCount", referenceIn.features.cols());
        this->inspector->addStat("ReferencePointCount", reference.features.cols());
        LOG_INFO_STREAM("PointMatcher::icp - reference pre-processing took " << t.elapsed() << " [s]");
        this->prefilteredReferencePtsCount = reference.features.cols();
        
        return computeWithTransformedReference(readingIn, reference, T_refIn_refMean, T_refIn_dataIn);
        
}
 
template<typename T>
typename PointMatcher<T>::TransformationParameters PointMatcher<T>::ICP::computeWithTransformedReference(
        const DataPoints& readingIn, 
        const DataPoints& reference, 
        const TransformationParameters& T_refIn_refMean,
        const TransformationParameters& T_refIn_dataIn)
{
        const int dim(reference.features.rows());
 
        if (T_refIn_dataIn.cols() != T_refIn_dataIn.rows()) {
                throw runtime_error("The initial transformation matrix must be squared.");
        }
        if (dim != T_refIn_dataIn.cols()) {
                throw runtime_error("The shape of initial transformation matrix must be NxN. "
                                                                                          "Where N is the number of rows in the read/reference scans.");
        }
 
        timer t; // Print how long take the algo
        
        // Apply readings filters
        // reading is express in frame <dataIn>
        DataPoints reading(readingIn);
        //const int nbPtsReading = reading.features.cols();
        this->readingDataPointsFilters.init();
        this->readingDataPointsFilters.apply(reading);
        readingFiltered = reading;
 
        // Reajust reading position: 
        // from here reading is express in frame <refMean>
        TransformationParameters 
                T_refMean_dataIn = T_refIn_refMean.inverse() * T_refIn_dataIn;
        this->transformations.apply(reading, T_refMean_dataIn);
        
        // Prepare reading filters used in the loop 
        this->readingStepDataPointsFilters.init();
        
        // Since reading and reference are express in <refMean>
        // the frame <refMean> is equivalent to the frame <iter(0)>
        TransformationParameters T_iter = Matrix::Identity(dim, dim);
        
        bool iterate(true);
        this->maxNumIterationsReached = false;
        this->transformationCheckers.init(T_iter, iterate);
 
        size_t iterationCount(0);
        
        // statistics on last step
        this->inspector->addStat("ReadingPreprocessingDuration", t.elapsed());
        this->inspector->addStat("ReadingInPointCount", readingIn.features.cols());
        this->inspector->addStat("ReadingPointCount", reading.features.cols());
        LOG_INFO_STREAM("PointMatcher::icp - reading pre-processing took " << t.elapsed() << " [s]");
        this->prefilteredReadingPtsCount = reading.features.cols();
        t.restart();
        
        // iterations
        while (iterate)
        {
                DataPoints stepReading(reading);
                
                //-----------------------------
                // Apply step filter
                this->readingStepDataPointsFilters.apply(stepReading);
                
                //-----------------------------
                // Transform Readings
                this->transformations.apply(stepReading, T_iter);
                
                //-----------------------------
                // Match to closest point in Reference
                const Matches matches(
                        this->matcher->findClosests(stepReading)
                );
                
                //-----------------------------
                // Detect outliers
                const OutlierWeights outlierWeights(
                        this->outlierFilters.compute(stepReading, reference, matches)
                );
                
                assert(outlierWeights.rows() == matches.ids.rows());
                assert(outlierWeights.cols() == matches.ids.cols());
                
                //cout << "outlierWeights: " << outlierWeights << "\n";
        
                
                //-----------------------------
                // Dump
                this->inspector->dumpIteration(
                        iterationCount, T_iter, reference, stepReading, matches, outlierWeights, this->transformationCheckers
                );
                
                //-----------------------------
                // Error minimization
                // equivalent to: 
                //   T_iter(i+1)_iter(0) = T_iter(i+1)_iter(i) * T_iter(i)_iter(0)
                T_iter = this->errorMinimizer->compute(
                        stepReading, reference, outlierWeights, matches) * T_iter;
                
                // Old version
                //T_iter = T_iter * this->errorMinimizer->compute(
                //      stepReading, reference, outlierWeights, matches);
                
                // in test
                try
                {
                        this->transformationCheckers.check(T_iter, iterate);
                }
                catch(const typename TransformationCheckersImpl<T>::CounterTransformationChecker::MaxNumIterationsReached &)
                {
                        iterate = false;
                        this->maxNumIterationsReached = true;
                }
        
                ++iterationCount;
        }
        
        this->inspector->addStat("IterationsCount", iterationCount);
        this->inspector->addStat("PointCountTouched", this->matcher->getVisitCount());
        this->matcher->resetVisitCount();
        this->inspector->addStat("OverlapRatio", this->errorMinimizer->getWeightedPointUsedRatio());
        this->inspector->addStat("ConvergenceDuration", t.elapsed());
        this->inspector->finish(iterationCount);
        
        LOG_INFO_STREAM("PointMatcher::icp - " << iterationCount << " iterations took " << t.elapsed() << " [s]");
        
        // Move transformation back to original coordinate (without center of mass)
        // T_iter is equivalent to: T_iter(i+1)_iter(0)
        // the frame <iter(0)> equals <refMean>
        // so we have: 
        //   T_iter(i+1)_dataIn = T_iter(i+1)_iter(0) * T_refMean_dataIn
        //   T_iter(i+1)_dataIn = T_iter(i+1)_iter(0) * T_iter(0)_dataIn
        // T_refIn_refMean remove the temperary frame added during initialization
        return (T_refIn_refMean * T_iter * T_refMean_dataIn);
}
 
template struct PointMatcher<float>::ICP;
template struct PointMatcher<double>::ICP;
 
 
template<typename T>
bool PointMatcher<T>::ICPSequence::hasMap() const
{
        return (mapPointCloud.features.cols() != 0);
}
 
template<typename T>
bool PointMatcher<T>::ICPSequence::setMap(const DataPoints& inputCloud)
{
        // Ensuring minimum definition of components
        if (!this->matcher)
                throw runtime_error("You must setup a matcher before running ICP");
        if (!this->inspector)
                throw runtime_error("You must setup an inspector before running ICP");
        
        timer t; // Print how long take the algo
        const int dim(inputCloud.features.rows());
        const int ptCount(inputCloud.features.cols());
        
        // update keyframe
        if (ptCount == 0)
        {
                LOG_WARNING_STREAM("Ignoring attempt to create a map from an empty cloud");
                return false;
        }
        
        this->inspector->addStat("MapPointCount", inputCloud.features.cols());
        
        // Set map
        mapPointCloud = inputCloud;
 
        // Create intermediate frame at the center of mass of reference pts cloud
        //  this help to solve for rotations
        const Vector meanMap = mapPointCloud.features.rowwise().sum() / ptCount;
        T_refIn_refMean = Matrix::Identity(dim, dim);
        T_refIn_refMean.block(0,dim-1, dim-1, 1) = meanMap.head(dim-1);
        
        // Reajust reference position (only translations): 
        // from here reference is express in frame <refMean>
        // Shortcut to do T_refIn_refMean.inverse() * reference
        mapPointCloud.features.topRows(dim-1).colwise() -= meanMap.head(dim-1);
 
        // Apply reference filters
        this->referenceDataPointsFilters.init();
        this->referenceDataPointsFilters.apply(mapPointCloud);
        
        this->matcher->init(mapPointCloud);
        
        this->inspector->addStat("SetMapDuration", t.elapsed());
        
        return true;
}
 
template<typename T>
void PointMatcher<T>::ICPSequence::clearMap()
{
        const int dim(mapPointCloud.features.rows());
        T_refIn_refMean = Matrix::Identity(dim, dim);
        mapPointCloud = DataPoints();
}
 
template<typename T>
void PointMatcher<T>::ICPSequence::setDefault()
{
        ICPChainBase::setDefault();
        
        if(mapPointCloud.getNbPoints() > 0)
        {
                this->matcher->init(mapPointCloud);
        }
}
 
template<typename T>
void PointMatcher<T>::ICPSequence::loadFromYaml(std::istream& in)
{
        ICPChainBase::loadFromYaml(in);
        
        if(mapPointCloud.getNbPoints() > 0)
        {
                this->matcher->init(mapPointCloud);
        }
}
 
template<typename T>
const typename PointMatcher<T>::DataPoints PointMatcher<T>::ICPSequence::getPrefilteredMap() const
{
        DataPoints globalMap(mapPointCloud);
        if(this->hasMap())
        {
                const int dim(mapPointCloud.features.rows());
                const Vector meanMapNonHomo(T_refIn_refMean.block(0,dim-1, dim-1, 1));
                globalMap.features.topRows(dim-1).colwise() += meanMapNonHomo;
        }
 
        return globalMap;
}
 
template<typename T>
const typename PointMatcher<T>::DataPoints PointMatcher<T>::ICPSequence::getMap() const {
        return PointMatcher<T>::ICPSequence::getPrefilteredMap();
}
 
template<typename T>
const typename PointMatcher<T>::DataPoints& PointMatcher<T>::ICPSequence::getPrefilteredInternalMap() const
{
        return mapPointCloud;
}
 
template<typename T>
const typename PointMatcher<T>::DataPoints& PointMatcher<T>::ICPSequence::getInternalMap() const {
        return PointMatcher<T>::ICPSequence::getPrefilteredInternalMap();
}
 
template<typename T>
typename PointMatcher<T>::TransformationParameters PointMatcher<T>::ICPSequence::operator ()(
        const DataPoints& cloudIn)
{
        const int dim = cloudIn.features.rows();
        const TransformationParameters identity = TransformationParameters::Identity(dim, dim);
        return this->compute(cloudIn, identity);
}
 
template<typename T>
typename PointMatcher<T>::TransformationParameters PointMatcher<T>::ICPSequence::operator ()(
        const DataPoints& cloudIn, const TransformationParameters& T_dataInOld_dataInNew)
{
        return this->compute(cloudIn, T_dataInOld_dataInNew);
}
 
template<typename T>
typename PointMatcher<T>::TransformationParameters PointMatcher<T>::ICPSequence::compute(
        const DataPoints& cloudIn, const TransformationParameters& T_refIn_dataIn)
{
        // initial keyframe
        if (!hasMap())
        {
                const int dim(cloudIn.features.rows());
                LOG_WARNING_STREAM("Ignoring attempt to perform ICP with an empty map");
                return Matrix::Identity(dim, dim);
        }
        
        this->inspector->init();
        
        return this->computeWithTransformedReference(cloudIn, mapPointCloud, T_refIn_refMean, T_refIn_dataIn);
}
 
template struct PointMatcher<float>::ICPSequence;
template struct PointMatcher<double>::ICPSequence;