FHWS/Fusion2016
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started working on the tex-part

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started working on eval-graphics
ned helper methods
tested some new aspects
some fixes and changes
added some graphics
new test-floorplan
many cleanups
This commit is contained in:
FrankE
2016-02-03 21:17:15 +01:00
parent 8a57b4cdbd
commit c5a5acbbf6
40 changed files with 69163 additions and 275 deletions
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63
code/eval/Eval.h
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@@ -18,50 +18,53 @@ public:
Eval() {
// Eval() {
pf = new K::ParticleFilter<MyState, MyControl, MyObservation>( MiscSettings::numParticles, std::unique_ptr<MyInitializer>(new MyInitializer(grid, 1120, 150, 3*350, 90)) );
// pf = new K::ParticleFilter<MyState, MyControl, MyObservation>( MiscSettings::numParticles, std::unique_ptr<MyInitializer>(new MyInitializer(grid, 1120, 150, 3*350, 90)) );
MyGridNode& start = (MyGridNode&)grid.getNodeFor(GridPoint(500,300,floors.h0.cm()));
MyGridNode& end = (MyGridNode&)grid.getNodeFor(GridPoint(7000,5000,floors.h3.cm()));
// MyGridNode& start = (MyGridNode&)grid.getNodeFor(GridPoint(500,300,floors.h0.cm()));
// MyGridNode& end = (MyGridNode&)grid.getNodeFor(GridPoint(7000,5000,floors.h3.cm()));
//GridWalkLightAtTheEndOfTheTunnel<MyGridNode>* walk = new GridWalkLightAtTheEndOfTheTunnel<MyGridNode>(grid, DijkstraMapper(grid), end);
//GridWalkRandomHeadingUpdate<MyGridNode>* walk = new GridWalkRandomHeadingUpdate<MyGridNode>();
GridWalkRandomHeadingUpdateAdv<MyGridNode>* walk = new GridWalkRandomHeadingUpdateAdv<MyGridNode>();
//GridWalkPushForward<MyGridNode>* walk = new GridWalkPushForward<MyGridNode>();
// //GridWalkRandomHeadingUpdate<MyGridNode>* walk = new GridWalkRandomHeadingUpdate<MyGridNode>();
// GridWalkRandomHeadingUpdateAdv<MyGridNode>* walk = new GridWalkRandomHeadingUpdateAdv<MyGridNode>();
// //GridWalkPushForward<MyGridNode>* walk = new GridWalkPushForward<MyGridNode>();
// //GridWalkLightAtTheEndOfTheTunnel<MyGridNode>* walk = new GridWalkLightAtTheEndOfTheTunnel<MyGridNode>(grid, DijkstraMapper(grid), end);
pf->setTransition( std::unique_ptr<MyTransition>( new MyTransition(grid, *walk)) );
// pf->setTransition( std::unique_ptr<MyTransition>( new MyTransition(grid, *walk)) );
sr = new SensorReader("./measurements/13/Galaxy/Path2/1433588396094.csv");
srt = new SensorReaderTurn("./measurements/13/Galaxy/Path2/Turns.txt");
srs = new SensorReaderStep("./measurements/13/Galaxy/Path2/Steps2.txt");
// sr = new SensorReader("./measurements/13/Galaxy/Path2/1433588396094.csv");
// srt = new SensorReaderTurn("./measurements/13/Galaxy/Path2/Turns.txt");
// srs = new SensorReaderStep("./measurements/13/Galaxy/Path2/Steps2.txt");
gtw = getGroundTruthWay(*sr, floors.gtwp, way2);
// gtw = getGroundTruthWay(*sr, floors.gtwp, way2);
}
// }
// //wifi also uniform dist 0/1 fuer bereiche die OK sind?
// //steps hochzaehlen weil mehr als einer in einer transition??
// //increase regional average region
// void setEval1() {
// runName = "TODO";
void setEval1() {
// // the particle filter's evaluation method
// std::unique_ptr<MyEvaluation> eval = std::unique_ptr<MyEvaluation>( new MyEvaluation() );
// eval.get()->setUsage(true, false, false, true, true);
// pf->setEvaluation( std::move(eval) );
// // resampling step?
// pf->setNEffThreshold(1.0);
// pf->setResampling( std::unique_ptr<K::ParticleFilterResamplingSimple<MyState>>(new K::ParticleFilterResamplingSimple<MyState>()) );
runName = "TODO";
// // state estimation step
// //pf->setEstimation( std::unique_ptr<K::ParticleFilterEstimationWeightedAverage<MyState>>(new K::ParticleFilterEstimationWeightedAverage<MyState>()));
// //pf->setEstimation( std::unique_ptr<K::ParticleFilterEstimationRegionalWeightedAverage<MyState>>(new K::ParticleFilterEstimationRegionalWeightedAverage<MyState>()));
// pf->setEstimation( std::unique_ptr<K::ParticleFilterEstimationOrderedWeightedAverage<MyState>>(new K::ParticleFilterEstimationOrderedWeightedAverage<MyState>(0.33f)));
// the particle filter's evaluation method
std::unique_ptr<MyEvaluation> eval = std::unique_ptr<MyEvaluation>( new MyEvaluation() );
eval.get()->setUsage(true, false, false, true, true);
pf->setEvaluation( std::move(eval) );
// resampling step?
pf->setNEffThreshold(1.0);
pf->setResampling( std::unique_ptr<K::ParticleFilterResamplingSimple<MyState>>(new K::ParticleFilterResamplingSimple<MyState>()) );
// state estimation step
pf->setEstimation( std::unique_ptr<K::ParticleFilterEstimationWeightedAverage<MyState>>(new K::ParticleFilterEstimationWeightedAverage<MyState>()));
//pf->setEstimation( std::unique_ptr<K::ParticleFilterEstimationRegionalWeightedAverage<MyState>>(new K::ParticleFilterEstimationRegionalWeightedAverage<MyState>()));
}
// }