added nav-mesh support via demo
This commit is contained in:
k-a-z-u
@@ -41,14 +41,15 @@ FILE(GLOB SOURCES
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./*/*.cpp
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./*/*/*.cpp
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./*/*/*/*.cpp
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../../Indoor/lib/tinyxml/tinyxml2.cpp
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../Indoor/lib/tinyxml/tinyxml2.cpp
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../Indoor/lib/Recast/*.cpp
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)
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# system specific compiler flags
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ADD_DEFINITIONS(
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-std=gnu++11
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#-std=gnu++14
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-Wall
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-Werror=return-type
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@@ -58,7 +59,7 @@ ADD_DEFINITIONS(
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-fstack-protector-all
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-g3
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-O2
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# -O2
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-march=native
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-DWITH_TESTS
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474
main.cpp
474
main.cpp
@@ -1,479 +1,9 @@
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#include <iostream>
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#include "filter/Structs.h"
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#include "filter/KLB.h"
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#include "Plotti.h"
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#include "filter/Logic.h"
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#include "Settings.h"
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#include <sys/types.h>
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#include <sys/stat.h>
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#include <Indoor/sensors/radio/model/WiFiModelFactory.h>
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#include <Indoor/sensors/radio/model/WiFiModelFactoryImpl.h>
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#include <Indoor/math/stats/Statistics.h>
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#include <Indoor/smc/smoothing/ForwardFilterHistory.h>
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#include <Indoor/smc/smoothing/FastKDESmoothing.h>
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//frank
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//const std::string mapDir = "/mnt/data/workspaces/IPIN2016/IPIN2016/competition/maps/";
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//const std::string dataDir = "/mnt/data/workspaces/IPIN2016/IPIN2016/competition/src/data/";
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//toni
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const std::string mapDir = "/home/toni/Documents/programme/localization/IndoorMap/maps/";
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//const std::string dataDir = "/home/toni/Documents/programme/localization/DynLag/code/data/";
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const std::string dataDir = "/home/toni/Documents/programme/localization/museum/measurements/shl/";
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//const std::string dataDir = "/home/toni/Documents/programme/localization/museum/measurements/motionAxisTest/";
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const std::string errorDir = dataDir + "results/";
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/** describes one dataset (map, training, parameter-estimation, ...) */
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struct DataSetup {
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std::string map;
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std::vector<std::string> training;
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std::string wifiParams;
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int minWifiOccurences;
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VAPGrouper::Mode vapMode;
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std::string grid;
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};
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/** all configured datasets */
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struct Data {
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DataSetup SecondFloorOnly = {
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mapDir + "SHL_Stock_2_01.xml",
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{
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dataDir + "Path1_1.csv",
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dataDir + "Path2_1.csv",
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dataDir + "Path3_1.csv",
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},
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mapDir + "wifi_fp_all.dat",
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40,
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VAPGrouper::Mode::LAST_MAC_DIGIT_TO_ZERO,
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mapDir + "grid_Stock_2_01.dat"
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};
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DataSetup FloorOneToThree = {
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mapDir + "SHL_Stock_1-3_03.xml",
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{
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dataDir + "Path4_0.csv",
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dataDir + "Path5_0.csv",
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dataDir + "Path6_0.csv",
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},
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mapDir + "wifi_fp_all.dat",
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40,
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VAPGrouper::Mode::LAST_MAC_DIGIT_TO_ZERO,
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mapDir + "grid_Stock_1-3_03.dat"
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};
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DataSetup MotionAxisTest = {
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mapDir + "SHL40_noElevator.xml",
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{
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dataDir + "Path0_0.csv"
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},
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mapDir + "wifi_fp_all.dat",
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40,
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VAPGrouper::Mode::LAST_MAC_DIGIT_TO_ZERO,
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mapDir + "grid_SHL40_noElevator.dat"
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};
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} data;
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Floorplan::IndoorMap* MyState::map;
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Stats::Statistics<float> run(DataSetup setup, int numFile, std::string folder, std::vector<int> gtPath) {
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std::vector<double> kld_data;
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// load the floorplan
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Floorplan::IndoorMap* map = Floorplan::Reader::readFromFile(setup.map);
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MyState::map = map;
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WiFiModelLogDistCeiling WiFiModel(map);
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WiFiModel.loadAPs(map, Settings::WiFiModel::TXP, Settings::WiFiModel::EXP, Settings::WiFiModel::WAF);
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Assert::isFalse(WiFiModel.getAllAPs().empty(), "no AccessPoints stored within the map.xml");
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//Wi-Fi model new
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// WiFiModelFactory factory(map);
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// WiFiModel* wifimodel= factory.loadXML("/home/toni/Documents/programme/localization/data/wifi/model/eachOptParPos_multimodel.xml");
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// Assert::isFalse(wifimodel->getAllAPs().empty(), "no AccessPoints stored within the map.xml");
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BeaconModelLogDistCeiling beaconModel(map);
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beaconModel.loadBeaconsFromMap(map, Settings::BeaconModel::TXP, Settings::BeaconModel::EXP, Settings::BeaconModel::WAF);
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//Assert::isFalse(beaconModel.getAllBeacons().empty(), "no Beacons stored within the map.xml");
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// build the grid
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std::ifstream inp(setup.grid, std::ifstream::binary);
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Grid<MyNode> grid(Settings::Grid::gridSize_cm);
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// grid.dat empty? -> build one and save it
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if (!inp.good() || (inp.peek()&&0) || inp.eof()) {
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std::ofstream onp;
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onp.open(setup.grid);
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GridFactory<MyNode> factory(grid);
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factory.build(map);
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// add node-importance
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Importance::addImportance(grid);
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grid.write(onp);
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} else {
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grid.read(inp);
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}
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// stamp WiFi signal-strengths onto the grid
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WiFiGridEstimator::estimate(grid, WiFiModel, Settings::smartphoneAboveGround);
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// reading file
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Offline::FileReader fr(setup.training[numFile]);
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//interpolator for ground truth
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Interpolator<uint64_t, Point3> gtInterpolator = fr.getGroundTruthPath(map, gtPath);
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//gnuplot plot
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Plotti plot;
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plot.addFloors(map);
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plot.addOutline(map);
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plot.addStairs(map);
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plot.gp << "set autoscale xy\n";
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//plot.addGrid(grid);
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plot.splot.getView().setEnabled(false);
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// init ctrl and observation
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MyControl ctrl;
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ctrl.resetAfterTransition();
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MyObs obs;
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//History of all estimated particles. Used for smoothing
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SMC::ForwardFilterHistory<MyState, MyControl, MyObs> pfHistory;
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//filter init
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SMC::ParticleFilterHistory<MyState, MyControl, MyObs> pf(Settings::numParticles, std::unique_ptr<PFInit>(new PFInit(grid)));
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//SMC::ParticleFilterHistory<MyState, MyControl, MyObs> pf(Settings::numParticles, std::unique_ptr<PFInitFixed>(new PFInitFixed(grid, GridPoint(55.5f * 100.0, 43.7f * 100.0, 740.0f), 180.0f)));
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pf.setTransition(std::unique_ptr<PFTrans>(new PFTrans(grid, &ctrl)));
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//pf.setTransition(std::unique_ptr<PFTransKLDSampling>(new PFTransKLDSampling(grid, &ctrl)));
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//pf.setTransition(std::unique_ptr<PFTransSimple>(new PFTransSimple(grid)));
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pf.setEvaluation(std::unique_ptr<PFEval>(new PFEval(WiFiModel, beaconModel, grid)));
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//resampling
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if(Settings::useKLB){
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pf.setResampling(std::unique_ptr<SMC::ParticleFilterResamplingDivergence<MyState>>(new SMC::ParticleFilterResamplingDivergence<MyState>()));
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} else {
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pf.setResampling(std::unique_ptr<SMC::ParticleFilterResamplingSimple<MyState>>(new SMC::ParticleFilterResamplingSimple<MyState>()));
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//pf.setResampling(std::unique_ptr<SMC::ParticleFilterResamplingPercent<MyState>>(new SMC::ParticleFilterResamplingPercent<MyState>(0.4)));
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//pf.setResampling(std::unique_ptr<NodeResampling<MyState, MyNode>>(new NodeResampling<MyState, MyNode>(*grid)););
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//pf.setResampling(std::unique_ptr<SMC::ParticleFilterResamplingKLD<MyState>>(new SMC::ParticleFilterResamplingKLD<MyState>()));
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}
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pf.setNEffThreshold(0.95);
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//estimation
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pf.setEstimation(std::unique_ptr<SMC::ParticleFilterEstimationWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationWeightedAverage<MyState>()));
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//pf.setEstimation(std::unique_ptr<SMC::ParticleFilterEstimationRegionalWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationRegionalWeightedAverage<MyState>()));
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//pf.setEstimation(std::unique_ptr<SMC::ParticleFilterEstimationOrderedWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationOrderedWeightedAverage<MyState>(0.5)));
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//pf.setEstimation(std::unique_ptr<SMC::ParticleFilterEstimationKernelDensity<MyState, 3>>(new SMC::ParticleFilterEstimationKernelDensity<MyState, 3>()));
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/** Smoothing Init */
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SMC::FastKDESmoothing<MyState, MyControl, MyObs> bf(Settings::numParticles, map, Settings::Grid::gridSize_cm, Settings::KDE::bandwidth);
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if(Settings::Smoothing::activated){
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//create the backward smoothing filter
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bf.setSampler( std::unique_ptr<SMC::CumulativeSampler<MyState>>(new SMC::CumulativeSampler<MyState>()));
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bool smoothing_resample = false;
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//bf->setNEffThreshold(1.0);
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if(smoothing_resample)
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bf.setResampling( std::unique_ptr<SMC::ParticleFilterResamplingSimple<MyState>>(new SMC::ParticleFilterResamplingSimple<MyState>()) );
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//bf.setTransition(std::unique_ptr<BFTrans>( new BFTrans) );
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bf.setTransition(std::unique_ptr<PFTrans>(new PFTrans(grid, &ctrl)));
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//Smoothing estimation
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bf.setEstimation(std::unique_ptr<SMC::ParticleFilterEstimationWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationWeightedAverage<MyState>()));
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//bf->setEstimation( std::unique_ptr<SMC::ParticleFilterEstimationRegionalWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationRegionalWeightedAverage<MyState>()));
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//bf->setEstimation( std::unique_ptr<SMC::ParticleFilterEstimationOrderedWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationOrderedWeightedAverage<MyState>(0.50f)));
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}
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Timestamp lastTimestamp = Timestamp::fromMS(0);
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StepDetection sd;
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PoseDetection pd;
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TurnDetection td(&pd);
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MotionDetection md;
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ActivityButterPressure act;
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//ActivityDetector act;
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RelativePressure relBaro;
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relBaro.setCalibrationTimeframe( Timestamp::fromMS(5000) );
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Stats::Statistics<float> errorStats;
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Stats::Statistics<float> errorStatsSmoothing;
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//file writing for error data
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const long int t = static_cast<long int>(time(NULL));
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const std::string evalDir = errorDir + folder + std::to_string(t);
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if(mkdir(evalDir.c_str(), S_IRWXU | S_IRWXG | S_IROTH | S_IXOTH) == -1){
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Assert::doThrow("Eval folder couldn't be created!");
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}
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std::ofstream errorFile;
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errorFile.open (evalDir + "/" + std::to_string(numFile) + "_" + std::to_string(t) + ".csv");
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std::ofstream errorFileSmoothing;
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errorFileSmoothing.open (evalDir + "/" + std::to_string(numFile) + "_" + std::to_string(t) + "_Smoothing.csv");
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// parse each sensor-value within the offline data
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for (const Offline::Entry& e : fr.getEntries()) {
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const Timestamp ts = Timestamp::fromMS(e.ts);
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if (e.type == Offline::Sensor::WIFI) {
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obs.wifi = fr.getWiFiGroupedByTime()[e.idx].data;
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} else if (e.type == Offline::Sensor::BEACON){
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obs.beacons.entries.push_back(fr.getBeacons()[e.idx].data);
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// remove to old beacon measurements
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obs.beacons.removeOld(ts);
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} else if (e.type == Offline::Sensor::ACC) {
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if (sd.add(ts, fr.getAccelerometer()[e.idx].data)) {
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++ctrl.numStepsSinceLastTransition;
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}
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const Offline::TS<AccelerometerData>& _acc = fr.getAccelerometer()[e.idx];
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pd.addAccelerometer(ts, _acc.data);
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} else if (e.type == Offline::Sensor::GYRO) {
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const Offline::TS<GyroscopeData>& _gyr = fr.getGyroscope()[e.idx];
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const float delta_gyro = td.addGyroscope(ts, _gyr.data);
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ctrl.turnSinceLastTransition_rad += delta_gyro;
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} else if (e.type == Offline::Sensor::BARO) {
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relBaro.add(ts, fr.getBarometer()[e.idx].data);
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obs.relativePressure = relBaro.getPressureRealtiveToStart();
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obs.sigmaPressure = relBaro.getSigma();
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//activity recognition
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act.add(ts, fr.getBarometer()[e.idx].data);
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obs.activity = act.get();
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//activity for transition
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} else if (e.type == Offline::Sensor::LIN_ACC) {
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md.addLinearAcceleration(ts, fr.getLinearAcceleration()[e.idx].data);
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} else if (e.type == Offline::Sensor::GRAVITY) {
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md.addGravity(ts, fr.getGravity()[e.idx].data);
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Eigen::Vector2f curVec = md.getCurrentMotionAxis();
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ctrl.motionDeltaAngle_rad = md.getMotionChangeInRad();
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}
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if (ts.ms() - lastTimestamp.ms() > 500) {
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/** filtering stuff */
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obs.currentTime = ts;
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MyState est = pf.update(&ctrl, obs);
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Point3 estPos = est.position.inMeter();
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Point3 gtPos = gtInterpolator.get(static_cast<uint64_t>(ts.ms()));
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/** plotting stuff */
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plot.pInterest.clear();
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plot.setEst(estPos);
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plot.setGT(gtPos);
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//plot.addEstimationNode(estPos);
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//plot.addParticles(pf.getParticles());
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/** error calculation stuff */
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float err_m = gtPos.getDistance(estPos);
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errorStats.add(err_m);
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errorFile << err_m << "\n";
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/** smoothing stuff */
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if(Settings::Smoothing::activated){
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// add everything from the forward step to the history
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pfHistory.add(ts, pf.getNonResamplingParticles(), ctrl, obs);
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//backward filtering
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//((BFTrans*)bf.getTransition())->setCurrentTime(tsHistory[(tsHistory.size() - 1) - i]);
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MyState estBF = bf.update(pfHistory, Settings::Smoothing::lag);
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// get ground truth position at lag time
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Point3 estPosSmoothing = estBF.position.inMeter();
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Point3 gtPosSmoothed;
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if(pfHistory.size() <= Settings::Smoothing::lag){
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gtPosSmoothed = gtInterpolator.get(static_cast<uint64_t>(pfHistory.getFirstTimestamp().ms()));
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} else {
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gtPosSmoothed = gtInterpolator.get(static_cast<uint64_t>(pfHistory.getTimestamp(Settings::Smoothing::lag).ms()));
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}
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//plot
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plot.addEstimationNodeSmoothed(estPosSmoothing);
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plot.addParticles(bf.getbackwardParticles().back());
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if(Settings::Smoothing::lag >= pfHistory.size()){
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// error between GT and smoothing
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float errSmoothing_m = gtPosSmoothed.getDistance(estPosSmoothing);
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errorStatsSmoothing.add(errSmoothing_m);
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errorFileSmoothing << errSmoothing_m << "\n";
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}
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}
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//plot misc
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plot.setTimeInMinute(static_cast<int>(ts.sec()) / 60, static_cast<int>(static_cast<int>(ts.sec())%60));
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if(Settings::useKLB){
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plot.gp << "set label 1002 at screen 0.04, 0.94 'KLD: " << ":" << kld_data.back() << "'\n";
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}
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plot.gp << "set label 1002 at screen 0.95, 0.98 'act:" << static_cast<int>(obs.activity) << "'\n";
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//draw gyro angle and motion angle
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//turn angle plot
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static float angleSumTurn = 0; angleSumTurn += ctrl.turnSinceLastTransition_rad;
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plot.showAngle(1, angleSumTurn + M_PI, Point2(0.9, 0.9), "Turn: ");
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//motion angle plot
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static float angleSumMotion = 0; angleSumMotion += ctrl.motionDeltaAngle_rad;
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plot.showAngle(2, angleSumMotion + M_PI, Point2(0.9, 0.8), "Motion: ");
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/** Draw everything */
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plot.show();
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usleep(10*10);
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lastTimestamp = ts;
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// reset control
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ctrl.resetAfterTransition();
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}
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}
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errorFile.close();
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std::cout << "Statistical Analysis Filtering: " << std::endl;
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std::cout << "Median: " << errorStats.getMedian() << " Average: " << errorStats.getAvg() << " Std: " << errorStats.getStdDev() << std::endl;
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std::cout << "Statistical Analysis Smoothing: " << std::endl;
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std::cout << "Median: " << errorStatsSmoothing.getMedian() << " Average: " << errorStatsSmoothing.getAvg() << " Std: " << errorStatsSmoothing.getStdDev() << std::endl;
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//Write the current plotti buffer into file
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std::ofstream plotFile;
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plotFile.open(evalDir + "/plot_" + std::to_string(numFile) + "_" + std::to_string(t) + ".gp");
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plot.saveToFile(plotFile);
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plotFile.close();
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for(int i = 0; i < map->floors.size(); ++i){
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plot.printSingleFloor(evalDir + "/image" + std::to_string(numFile) + "_" + std::to_string(t), i);
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plot.show();
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usleep(10*10);
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}
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plot.printSideView(evalDir + "/image" + std::to_string(numFile) + "_" + std::to_string(t), 90);
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||||
plot.show();
|
||||
|
||||
plot.printSideView(evalDir + "/image" + std::to_string(numFile) + "_" + std::to_string(t), 0);
|
||||
plot.show();
|
||||
|
||||
plot.printOverview(evalDir + "/image" + std::to_string(numFile) + "_" + std::to_string(t));
|
||||
plot.show();
|
||||
|
||||
|
||||
/** Draw KLB */
|
||||
K::Gnuplot gp;
|
||||
K::GnuplotPlot plotkld;
|
||||
K::GnuplotPlotElementLines lines;
|
||||
if(Settings::useKLB){
|
||||
|
||||
std::string path = evalDir + "/image" + std::to_string(numFile) + "_" + std::to_string(t);
|
||||
gp << "set terminal png size 1280,720\n";
|
||||
gp << "set output '" << path << "_shennendistance.png'\n";
|
||||
|
||||
for(int i=0; i < kld_data.size()-1; ++i){
|
||||
|
||||
K::GnuplotPoint2 p1(i, kld_data[i]);
|
||||
K::GnuplotPoint2 p2(i+1, kld_data[i+1]);
|
||||
|
||||
lines.addSegment(p1, p2);
|
||||
}
|
||||
|
||||
plotkld.add(&lines);
|
||||
gp.draw(plotkld);
|
||||
gp.flush();
|
||||
plot.splot.getView().setEnabled(false);
|
||||
}
|
||||
|
||||
std::cout << "finished" << std::endl;
|
||||
sleep(1);
|
||||
|
||||
return errorStats;
|
||||
|
||||
}
|
||||
#include "navMesh/main.h"
|
||||
|
||||
int main(int argc, char** argv) {
|
||||
|
||||
Stats::Statistics<float> statsAVG;
|
||||
Stats::Statistics<float> statsMedian;
|
||||
Stats::Statistics<float> statsSTD;
|
||||
Stats::Statistics<float> statsQuantil;
|
||||
Stats::Statistics<float> tmp;
|
||||
|
||||
for(int i = 0; i < 10; ++i){
|
||||
|
||||
tmp = run(data.SecondFloorOnly, 0, "KDE-Smoothing-Test", Settings::Path_DongleTest::path1);
|
||||
statsMedian.add(tmp.getMedian());
|
||||
statsAVG.add(tmp.getAvg());
|
||||
statsSTD.add(tmp.getStdDev());
|
||||
statsQuantil.add(tmp.getQuantile(0.75));
|
||||
|
||||
// tmp = run(data.MotionAxisTest, 0, "Motion-Axis-Test", Settings::Path_DongleTest::path1);
|
||||
// statsMedian.add(tmp.getMedian());
|
||||
// statsAVG.add(tmp.getAvg());
|
||||
// statsSTD.add(tmp.getStdDev());
|
||||
// statsQuantil.add(tmp.getQuantile(0.75));
|
||||
|
||||
std::cout << "Iteration " << i << " completed" << std::endl;;
|
||||
}
|
||||
|
||||
std::cout << "==========================================================" << std::endl;
|
||||
std::cout << "Average of all statistical data: " << std::endl;
|
||||
std::cout << "Median: " << statsMedian.getAvg() << std::endl;
|
||||
std::cout << "Average: " << statsAVG.getAvg() << std::endl;
|
||||
std::cout << "Standard Deviation: " << statsSTD.getAvg() << std::endl;
|
||||
std::cout << "75 Quantil: " << statsQuantil.getAvg() << std::endl;
|
||||
std::cout << "==========================================================" << std::endl;
|
||||
|
||||
//EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS
|
||||
std::ofstream finalStatisticFile;
|
||||
finalStatisticFile.open (errorDir + "/tmp.csv");
|
||||
|
||||
finalStatisticFile << "Average of all statistical data: \n";
|
||||
finalStatisticFile << "Median: " << statsMedian.getAvg() << "\n";
|
||||
finalStatisticFile << "Average: " << statsAVG.getAvg() << "\n";
|
||||
finalStatisticFile << "Standard Deviation: " << statsSTD.getAvg() << "\n";
|
||||
finalStatisticFile << "75 Quantil: " << statsQuantil.getAvg() << "\n";
|
||||
|
||||
finalStatisticFile.close();
|
||||
//EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS
|
||||
navMeshMain();
|
||||
|
||||
}
|
||||
|
||||
494
mainToni.h
Normal file
494
mainToni.h
Normal file
@@ -0,0 +1,494 @@
|
||||
#ifndef MAINTONI_H
|
||||
#define MAINTONI_H
|
||||
|
||||
#include <iostream>
|
||||
|
||||
#include "filter/Structs.h"
|
||||
#include "filter/KLB.h"
|
||||
#include "Plotti.h"
|
||||
#include "filter/Logic.h"
|
||||
#include "Settings.h"
|
||||
|
||||
#include <sys/types.h>
|
||||
#include <sys/stat.h>
|
||||
|
||||
#include <Indoor/sensors/radio/model/WiFiModelFactory.h>
|
||||
#include <Indoor/sensors/radio/model/WiFiModelFactoryImpl.h>
|
||||
#include <Indoor/math/stats/Statistics.h>
|
||||
#include <Indoor/smc/smoothing/ForwardFilterHistory.h>
|
||||
|
||||
#include <Indoor/smc/smoothing/FastKDESmoothing.h>
|
||||
|
||||
#include "navMesh/main.h"
|
||||
|
||||
#define D_TONI 1
|
||||
#define D_FRANK 2
|
||||
#define USE_DATA D_FRANK
|
||||
|
||||
#if (USE_DATA == D_FRANK)
|
||||
//const std::string mapDir = "/mnt/data/workspaces/IPIN2016/IPIN2016/competition/maps/";
|
||||
//const std::string dataDir = "/mnt/data/workspaces/IPIN2016/IPIN2016/competition/src/data/";
|
||||
const std::string mapDir = "/apps/museum/maps/";
|
||||
const std::string dataDir = "/apps/museum/data/";
|
||||
const std::string errorDir = dataDir + "results/";
|
||||
#elif (USE_DATA == D_TONI)
|
||||
const std::string mapDir = "/home/toni/Documents/programme/localization/IndoorMap/maps/";
|
||||
//const std::string dataDir = "/home/toni/Documents/programme/localization/DynLag/code/data/";
|
||||
const std::string dataDir = "/home/toni/Documents/programme/localization/museum/measurements/shl/";
|
||||
//const std::string dataDir = "/home/toni/Documents/programme/localization/museum/measurements/motionAxisTest/";
|
||||
const std::string errorDir = dataDir + "results/";
|
||||
#endif
|
||||
|
||||
/** describes one dataset (map, training, parameter-estimation, ...) */
|
||||
struct DataSetup {
|
||||
std::string map;
|
||||
std::vector<std::string> training;
|
||||
std::string wifiParams;
|
||||
int minWifiOccurences;
|
||||
VAPGrouper::Mode vapMode;
|
||||
std::string grid;
|
||||
};
|
||||
|
||||
/** all configured datasets */
|
||||
struct Data {
|
||||
|
||||
DataSetup SecondFloorOnly = {
|
||||
|
||||
mapDir + "SHL_Stock_2_01.xml",
|
||||
|
||||
{
|
||||
dataDir + "Path1_1.csv",
|
||||
dataDir + "Path2_1.csv",
|
||||
dataDir + "Path3_1.csv",
|
||||
},
|
||||
|
||||
mapDir + "wifi_fp_all.dat",
|
||||
40,
|
||||
VAPGrouper::Mode::LAST_MAC_DIGIT_TO_ZERO,
|
||||
mapDir + "grid_Stock_2_01.dat"
|
||||
};
|
||||
|
||||
DataSetup FloorOneToThree = {
|
||||
|
||||
mapDir + "SHL_Stock_1-3_03.xml",
|
||||
|
||||
{
|
||||
dataDir + "Path4_0.csv",
|
||||
dataDir + "Path5_0.csv",
|
||||
dataDir + "Path6_0.csv",
|
||||
},
|
||||
|
||||
mapDir + "wifi_fp_all.dat",
|
||||
40,
|
||||
VAPGrouper::Mode::LAST_MAC_DIGIT_TO_ZERO,
|
||||
mapDir + "grid_Stock_1-3_03.dat"
|
||||
};
|
||||
|
||||
DataSetup MotionAxisTest = {
|
||||
|
||||
mapDir + "SHL40_noElevator.xml",
|
||||
|
||||
{
|
||||
dataDir + "Path0_0.csv"
|
||||
},
|
||||
|
||||
mapDir + "wifi_fp_all.dat",
|
||||
40,
|
||||
VAPGrouper::Mode::LAST_MAC_DIGIT_TO_ZERO,
|
||||
mapDir + "grid_SHL40_noElevator.dat"
|
||||
};
|
||||
|
||||
} data;
|
||||
|
||||
Floorplan::IndoorMap* MyState::map;
|
||||
|
||||
Stats::Statistics<float> run(DataSetup setup, int numFile, std::string folder, std::vector<int> gtPath) {
|
||||
|
||||
std::vector<double> kld_data;
|
||||
|
||||
// load the floorplan
|
||||
Floorplan::IndoorMap* map = Floorplan::Reader::readFromFile(setup.map);
|
||||
MyState::map = map;
|
||||
|
||||
WiFiModelLogDistCeiling WiFiModel(map);
|
||||
WiFiModel.loadAPs(map, Settings::WiFiModel::TXP, Settings::WiFiModel::EXP, Settings::WiFiModel::WAF);
|
||||
Assert::isFalse(WiFiModel.getAllAPs().empty(), "no AccessPoints stored within the map.xml");
|
||||
|
||||
//Wi-Fi model new
|
||||
// WiFiModelFactory factory(map);
|
||||
// WiFiModel* wifimodel= factory.loadXML("/home/toni/Documents/programme/localization/data/wifi/model/eachOptParPos_multimodel.xml");
|
||||
// Assert::isFalse(wifimodel->getAllAPs().empty(), "no AccessPoints stored within the map.xml");
|
||||
|
||||
BeaconModelLogDistCeiling beaconModel(map);
|
||||
beaconModel.loadBeaconsFromMap(map, Settings::BeaconModel::TXP, Settings::BeaconModel::EXP, Settings::BeaconModel::WAF);
|
||||
//Assert::isFalse(beaconModel.getAllBeacons().empty(), "no Beacons stored within the map.xml");
|
||||
|
||||
|
||||
// build the grid
|
||||
std::ifstream inp(setup.grid, std::ifstream::binary);
|
||||
Grid<MyNode> grid(Settings::Grid::gridSize_cm);
|
||||
|
||||
// grid.dat empty? -> build one and save it
|
||||
if (!inp.good() || (inp.peek()&&0) || inp.eof()) {
|
||||
std::ofstream onp;
|
||||
onp.open(setup.grid);
|
||||
GridFactory<MyNode> factory(grid);
|
||||
factory.build(map);
|
||||
|
||||
// add node-importance
|
||||
Importance::addImportance(grid);
|
||||
|
||||
grid.write(onp);
|
||||
} else {
|
||||
grid.read(inp);
|
||||
}
|
||||
|
||||
// stamp WiFi signal-strengths onto the grid
|
||||
WiFiGridEstimator::estimate(grid, WiFiModel, Settings::smartphoneAboveGround);
|
||||
|
||||
// reading file
|
||||
Offline::FileReader fr(setup.training[numFile]);
|
||||
|
||||
//interpolator for ground truth
|
||||
Interpolator<uint64_t, Point3> gtInterpolator = fr.getGroundTruthPath(map, gtPath);
|
||||
|
||||
//gnuplot plot
|
||||
Plotti plot;
|
||||
plot.addFloors(map);
|
||||
plot.addOutline(map);
|
||||
plot.addStairs(map);
|
||||
plot.gp << "set autoscale xy\n";
|
||||
//plot.addGrid(grid);
|
||||
plot.splot.getView().setEnabled(false);
|
||||
|
||||
// init ctrl and observation
|
||||
MyControl ctrl;
|
||||
ctrl.resetAfterTransition();
|
||||
MyObs obs;
|
||||
|
||||
//History of all estimated particles. Used for smoothing
|
||||
SMC::ForwardFilterHistory<MyState, MyControl, MyObs> pfHistory;
|
||||
|
||||
//filter init
|
||||
SMC::ParticleFilterHistory<MyState, MyControl, MyObs> pf(Settings::numParticles, std::unique_ptr<PFInit>(new PFInit(grid)));
|
||||
//SMC::ParticleFilterHistory<MyState, MyControl, MyObs> pf(Settings::numParticles, std::unique_ptr<PFInitFixed>(new PFInitFixed(grid, GridPoint(55.5f * 100.0, 43.7f * 100.0, 740.0f), 180.0f)));
|
||||
|
||||
pf.setTransition(std::unique_ptr<PFTrans>(new PFTrans(grid, &ctrl)));
|
||||
//pf.setTransition(std::unique_ptr<PFTransKLDSampling>(new PFTransKLDSampling(grid, &ctrl)));
|
||||
//pf.setTransition(std::unique_ptr<PFTransSimple>(new PFTransSimple(grid)));
|
||||
pf.setEvaluation(std::unique_ptr<PFEval>(new PFEval(WiFiModel, beaconModel, grid)));
|
||||
|
||||
//resampling
|
||||
if(Settings::useKLB){
|
||||
pf.setResampling(std::unique_ptr<SMC::ParticleFilterResamplingDivergence<MyState>>(new SMC::ParticleFilterResamplingDivergence<MyState>()));
|
||||
} else {
|
||||
pf.setResampling(std::unique_ptr<SMC::ParticleFilterResamplingSimple<MyState>>(new SMC::ParticleFilterResamplingSimple<MyState>()));
|
||||
//pf.setResampling(std::unique_ptr<SMC::ParticleFilterResamplingPercent<MyState>>(new SMC::ParticleFilterResamplingPercent<MyState>(0.4)));
|
||||
//pf.setResampling(std::unique_ptr<NodeResampling<MyState, MyNode>>(new NodeResampling<MyState, MyNode>(*grid)););
|
||||
//pf.setResampling(std::unique_ptr<SMC::ParticleFilterResamplingKLD<MyState>>(new SMC::ParticleFilterResamplingKLD<MyState>()));
|
||||
}
|
||||
|
||||
pf.setNEffThreshold(0.95);
|
||||
|
||||
//estimation
|
||||
pf.setEstimation(std::unique_ptr<SMC::ParticleFilterEstimationWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationWeightedAverage<MyState>()));
|
||||
//pf.setEstimation(std::unique_ptr<SMC::ParticleFilterEstimationRegionalWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationRegionalWeightedAverage<MyState>()));
|
||||
//pf.setEstimation(std::unique_ptr<SMC::ParticleFilterEstimationOrderedWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationOrderedWeightedAverage<MyState>(0.5)));
|
||||
//pf.setEstimation(std::unique_ptr<SMC::ParticleFilterEstimationKernelDensity<MyState, 3>>(new SMC::ParticleFilterEstimationKernelDensity<MyState, 3>()));
|
||||
|
||||
|
||||
/** Smoothing Init */
|
||||
SMC::FastKDESmoothing<MyState, MyControl, MyObs> bf(Settings::numParticles, map, Settings::Grid::gridSize_cm, Settings::KDE::bandwidth);
|
||||
if(Settings::Smoothing::activated){
|
||||
|
||||
//create the backward smoothing filter
|
||||
bf.setSampler( std::unique_ptr<SMC::CumulativeSampler<MyState>>(new SMC::CumulativeSampler<MyState>()));
|
||||
|
||||
bool smoothing_resample = false;
|
||||
//bf->setNEffThreshold(1.0);
|
||||
if(smoothing_resample)
|
||||
bf.setResampling( std::unique_ptr<SMC::ParticleFilterResamplingSimple<MyState>>(new SMC::ParticleFilterResamplingSimple<MyState>()) );
|
||||
|
||||
//bf.setTransition(std::unique_ptr<BFTrans>( new BFTrans) );
|
||||
bf.setTransition(std::unique_ptr<PFTrans>(new PFTrans(grid, &ctrl)));
|
||||
|
||||
//Smoothing estimation
|
||||
bf.setEstimation(std::unique_ptr<SMC::ParticleFilterEstimationWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationWeightedAverage<MyState>()));
|
||||
//bf->setEstimation( std::unique_ptr<SMC::ParticleFilterEstimationRegionalWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationRegionalWeightedAverage<MyState>()));
|
||||
//bf->setEstimation( std::unique_ptr<SMC::ParticleFilterEstimationOrderedWeightedAverage<MyState>>(new SMC::ParticleFilterEstimationOrderedWeightedAverage<MyState>(0.50f)));
|
||||
}
|
||||
|
||||
|
||||
|
||||
Timestamp lastTimestamp = Timestamp::fromMS(0);
|
||||
|
||||
StepDetection sd;
|
||||
PoseDetection pd;
|
||||
TurnDetection td(&pd);
|
||||
MotionDetection md;
|
||||
ActivityButterPressure act;
|
||||
//ActivityDetector act;
|
||||
|
||||
RelativePressure relBaro;
|
||||
relBaro.setCalibrationTimeframe( Timestamp::fromMS(5000) );
|
||||
|
||||
Stats::Statistics<float> errorStats;
|
||||
Stats::Statistics<float> errorStatsSmoothing;
|
||||
|
||||
//file writing for error data
|
||||
const long int t = static_cast<long int>(time(NULL));
|
||||
const std::string evalDir = errorDir + folder + std::to_string(t);
|
||||
if(mkdir(evalDir.c_str(), S_IRWXU | S_IRWXG | S_IROTH | S_IXOTH) == -1){
|
||||
Assert::doThrow("Eval folder couldn't be created!");
|
||||
}
|
||||
|
||||
std::ofstream errorFile;
|
||||
errorFile.open (evalDir + "/" + std::to_string(numFile) + "_" + std::to_string(t) + ".csv");
|
||||
|
||||
std::ofstream errorFileSmoothing;
|
||||
errorFileSmoothing.open (evalDir + "/" + std::to_string(numFile) + "_" + std::to_string(t) + "_Smoothing.csv");
|
||||
|
||||
// parse each sensor-value within the offline data
|
||||
for (const Offline::Entry& e : fr.getEntries()) {
|
||||
|
||||
const Timestamp ts = Timestamp::fromMS(e.ts);
|
||||
|
||||
if (e.type == Offline::Sensor::WIFI) {
|
||||
obs.wifi = fr.getWiFiGroupedByTime()[e.idx].data;
|
||||
|
||||
} else if (e.type == Offline::Sensor::BEACON){
|
||||
obs.beacons.entries.push_back(fr.getBeacons()[e.idx].data);
|
||||
|
||||
// remove to old beacon measurements
|
||||
obs.beacons.removeOld(ts);
|
||||
|
||||
} else if (e.type == Offline::Sensor::ACC) {
|
||||
if (sd.add(ts, fr.getAccelerometer()[e.idx].data)) {
|
||||
++ctrl.numStepsSinceLastTransition;
|
||||
}
|
||||
const Offline::TS<AccelerometerData>& _acc = fr.getAccelerometer()[e.idx];
|
||||
pd.addAccelerometer(ts, _acc.data);
|
||||
|
||||
} else if (e.type == Offline::Sensor::GYRO) {
|
||||
const Offline::TS<GyroscopeData>& _gyr = fr.getGyroscope()[e.idx];
|
||||
const float delta_gyro = td.addGyroscope(ts, _gyr.data);
|
||||
|
||||
ctrl.turnSinceLastTransition_rad += delta_gyro;
|
||||
|
||||
} else if (e.type == Offline::Sensor::BARO) {
|
||||
relBaro.add(ts, fr.getBarometer()[e.idx].data);
|
||||
obs.relativePressure = relBaro.getPressureRealtiveToStart();
|
||||
obs.sigmaPressure = relBaro.getSigma();
|
||||
|
||||
//activity recognition
|
||||
act.add(ts, fr.getBarometer()[e.idx].data);
|
||||
obs.activity = act.get();
|
||||
//activity for transition
|
||||
|
||||
} else if (e.type == Offline::Sensor::LIN_ACC) {
|
||||
md.addLinearAcceleration(ts, fr.getLinearAcceleration()[e.idx].data);
|
||||
|
||||
} else if (e.type == Offline::Sensor::GRAVITY) {
|
||||
md.addGravity(ts, fr.getGravity()[e.idx].data);
|
||||
Eigen::Vector2f curVec = md.getCurrentMotionAxis();
|
||||
ctrl.motionDeltaAngle_rad = md.getMotionChangeInRad();
|
||||
}
|
||||
|
||||
if (ts.ms() - lastTimestamp.ms() > 500) {
|
||||
|
||||
|
||||
/** filtering stuff */
|
||||
obs.currentTime = ts;
|
||||
MyState est = pf.update(&ctrl, obs);
|
||||
|
||||
Point3 estPos = est.position.inMeter();
|
||||
Point3 gtPos = gtInterpolator.get(static_cast<uint64_t>(ts.ms()));
|
||||
|
||||
/** plotting stuff */
|
||||
plot.pInterest.clear();
|
||||
|
||||
plot.setEst(estPos);
|
||||
plot.setGT(gtPos);
|
||||
//plot.addEstimationNode(estPos);
|
||||
//plot.addParticles(pf.getParticles());
|
||||
|
||||
/** error calculation stuff */
|
||||
float err_m = gtPos.getDistance(estPos);
|
||||
errorStats.add(err_m);
|
||||
errorFile << err_m << "\n";
|
||||
|
||||
|
||||
/** smoothing stuff */
|
||||
if(Settings::Smoothing::activated){
|
||||
|
||||
// add everything from the forward step to the history
|
||||
pfHistory.add(ts, pf.getNonResamplingParticles(), ctrl, obs);
|
||||
|
||||
//backward filtering
|
||||
//((BFTrans*)bf.getTransition())->setCurrentTime(tsHistory[(tsHistory.size() - 1) - i]);
|
||||
MyState estBF = bf.update(pfHistory, Settings::Smoothing::lag);
|
||||
|
||||
// get ground truth position at lag time
|
||||
Point3 estPosSmoothing = estBF.position.inMeter();
|
||||
Point3 gtPosSmoothed;
|
||||
if(pfHistory.size() <= Settings::Smoothing::lag){
|
||||
gtPosSmoothed = gtInterpolator.get(static_cast<uint64_t>(pfHistory.getFirstTimestamp().ms()));
|
||||
} else {
|
||||
gtPosSmoothed = gtInterpolator.get(static_cast<uint64_t>(pfHistory.getTimestamp(Settings::Smoothing::lag).ms()));
|
||||
}
|
||||
|
||||
|
||||
//plot
|
||||
plot.addEstimationNodeSmoothed(estPosSmoothing);
|
||||
plot.addParticles(bf.getbackwardParticles().back());
|
||||
|
||||
|
||||
if(Settings::Smoothing::lag >= pfHistory.size()){
|
||||
// error between GT and smoothing
|
||||
float errSmoothing_m = gtPosSmoothed.getDistance(estPosSmoothing);
|
||||
errorStatsSmoothing.add(errSmoothing_m);
|
||||
errorFileSmoothing << errSmoothing_m << "\n";
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
//plot misc
|
||||
plot.setTimeInMinute(static_cast<int>(ts.sec()) / 60, static_cast<int>(static_cast<int>(ts.sec())%60));
|
||||
|
||||
if(Settings::useKLB){
|
||||
plot.gp << "set label 1002 at screen 0.04, 0.94 'KLD: " << ":" << kld_data.back() << "'\n";
|
||||
}
|
||||
plot.gp << "set label 1002 at screen 0.95, 0.98 'act:" << static_cast<int>(obs.activity) << "'\n";
|
||||
|
||||
//draw gyro angle and motion angle
|
||||
//turn angle plot
|
||||
static float angleSumTurn = 0; angleSumTurn += ctrl.turnSinceLastTransition_rad;
|
||||
plot.showAngle(1, angleSumTurn + M_PI, Point2(0.9, 0.9), "Turn: ");
|
||||
|
||||
//motion angle plot
|
||||
static float angleSumMotion = 0; angleSumMotion += ctrl.motionDeltaAngle_rad;
|
||||
plot.showAngle(2, angleSumMotion + M_PI, Point2(0.9, 0.8), "Motion: ");
|
||||
|
||||
/** Draw everything */
|
||||
plot.show();
|
||||
usleep(10*10);
|
||||
|
||||
lastTimestamp = ts;
|
||||
|
||||
// reset control
|
||||
ctrl.resetAfterTransition();
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
errorFile.close();
|
||||
|
||||
std::cout << "Statistical Analysis Filtering: " << std::endl;
|
||||
std::cout << "Median: " << errorStats.getMedian() << " Average: " << errorStats.getAvg() << " Std: " << errorStats.getStdDev() << std::endl;
|
||||
|
||||
std::cout << "Statistical Analysis Smoothing: " << std::endl;
|
||||
std::cout << "Median: " << errorStatsSmoothing.getMedian() << " Average: " << errorStatsSmoothing.getAvg() << " Std: " << errorStatsSmoothing.getStdDev() << std::endl;
|
||||
|
||||
//Write the current plotti buffer into file
|
||||
std::ofstream plotFile;
|
||||
plotFile.open(evalDir + "/plot_" + std::to_string(numFile) + "_" + std::to_string(t) + ".gp");
|
||||
plot.saveToFile(plotFile);
|
||||
plotFile.close();
|
||||
|
||||
for(int i = 0; i < map->floors.size(); ++i){
|
||||
plot.printSingleFloor(evalDir + "/image" + std::to_string(numFile) + "_" + std::to_string(t), i);
|
||||
plot.show();
|
||||
usleep(10*10);
|
||||
}
|
||||
|
||||
plot.printSideView(evalDir + "/image" + std::to_string(numFile) + "_" + std::to_string(t), 90);
|
||||
plot.show();
|
||||
|
||||
plot.printSideView(evalDir + "/image" + std::to_string(numFile) + "_" + std::to_string(t), 0);
|
||||
plot.show();
|
||||
|
||||
plot.printOverview(evalDir + "/image" + std::to_string(numFile) + "_" + std::to_string(t));
|
||||
plot.show();
|
||||
|
||||
|
||||
/** Draw KLB */
|
||||
K::Gnuplot gp;
|
||||
K::GnuplotPlot plotkld;
|
||||
K::GnuplotPlotElementLines lines;
|
||||
if(Settings::useKLB){
|
||||
|
||||
std::string path = evalDir + "/image" + std::to_string(numFile) + "_" + std::to_string(t);
|
||||
gp << "set terminal png size 1280,720\n";
|
||||
gp << "set output '" << path << "_shennendistance.png'\n";
|
||||
|
||||
for(int i=0; i < kld_data.size()-1; ++i){
|
||||
|
||||
K::GnuplotPoint2 p1(i, kld_data[i]);
|
||||
K::GnuplotPoint2 p2(i+1, kld_data[i+1]);
|
||||
|
||||
lines.addSegment(p1, p2);
|
||||
}
|
||||
|
||||
plotkld.add(&lines);
|
||||
gp.draw(plotkld);
|
||||
gp.flush();
|
||||
plot.splot.getView().setEnabled(false);
|
||||
}
|
||||
|
||||
std::cout << "finished" << std::endl;
|
||||
sleep(1);
|
||||
|
||||
return errorStats;
|
||||
|
||||
}
|
||||
|
||||
int main(int argc, char** argv) {
|
||||
|
||||
Stats::Statistics<float> statsAVG;
|
||||
Stats::Statistics<float> statsMedian;
|
||||
Stats::Statistics<float> statsSTD;
|
||||
Stats::Statistics<float> statsQuantil;
|
||||
Stats::Statistics<float> tmp;
|
||||
|
||||
for(int i = 0; i < 10; ++i){
|
||||
|
||||
tmp = run(data.SecondFloorOnly, 0, "KDE-Smoothing-Test", Settings::Path_DongleTest::path1);
|
||||
statsMedian.add(tmp.getMedian());
|
||||
statsAVG.add(tmp.getAvg());
|
||||
statsSTD.add(tmp.getStdDev());
|
||||
statsQuantil.add(tmp.getQuantile(0.75));
|
||||
|
||||
// tmp = run(data.MotionAxisTest, 0, "Motion-Axis-Test", Settings::Path_DongleTest::path1);
|
||||
// statsMedian.add(tmp.getMedian());
|
||||
// statsAVG.add(tmp.getAvg());
|
||||
// statsSTD.add(tmp.getStdDev());
|
||||
// statsQuantil.add(tmp.getQuantile(0.75));
|
||||
|
||||
std::cout << "Iteration " << i << " completed" << std::endl;;
|
||||
}
|
||||
|
||||
std::cout << "==========================================================" << std::endl;
|
||||
std::cout << "Average of all statistical data: " << std::endl;
|
||||
std::cout << "Median: " << statsMedian.getAvg() << std::endl;
|
||||
std::cout << "Average: " << statsAVG.getAvg() << std::endl;
|
||||
std::cout << "Standard Deviation: " << statsSTD.getAvg() << std::endl;
|
||||
std::cout << "75 Quantil: " << statsQuantil.getAvg() << std::endl;
|
||||
std::cout << "==========================================================" << std::endl;
|
||||
|
||||
//EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS
|
||||
std::ofstream finalStatisticFile;
|
||||
finalStatisticFile.open (errorDir + "/tmp.csv");
|
||||
|
||||
finalStatisticFile << "Average of all statistical data: \n";
|
||||
finalStatisticFile << "Median: " << statsMedian.getAvg() << "\n";
|
||||
finalStatisticFile << "Average: " << statsAVG.getAvg() << "\n";
|
||||
finalStatisticFile << "Standard Deviation: " << statsSTD.getAvg() << "\n";
|
||||
finalStatisticFile << "75 Quantil: " << statsQuantil.getAvg() << "\n";
|
||||
|
||||
finalStatisticFile.close();
|
||||
//EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS EDIT THIS
|
||||
|
||||
}
|
||||
|
||||
|
||||
#endif // MAINTONI_H
|
||||
184
navMesh/filter.h
Normal file
184
navMesh/filter.h
Normal file
@@ -0,0 +1,184 @@
|
||||
#ifndef NAV_MESH_FILTER_H
|
||||
#define NAV_MESH_FILTER_H
|
||||
|
||||
#include "mesh.h"
|
||||
|
||||
#include <Indoor/geo/Heading.h>
|
||||
#include <Indoor/math/Distributions.h>
|
||||
|
||||
#include <KLib/math/filter/particles/Particle.h>
|
||||
#include <KLib/math/filter/particles/ParticleFilter.h>
|
||||
#include <KLib/math/filter/particles/ParticleFilterEvaluation.h>
|
||||
#include <KLib/math/filter/particles/ParticleFilterInitializer.h>
|
||||
#include <KLib/math/filter/particles/resampling/ParticleFilterResamplingSimple.h>
|
||||
#include <KLib/math/filter/particles/estimation/ParticleFilterEstimationWeightedAverage.h>
|
||||
|
||||
#include <Indoor/navMesh/walk/NavMeshWalkSimple.h>
|
||||
#include <Indoor/navMesh/walk/NavMeshWalkEval.h>
|
||||
|
||||
struct MyState {
|
||||
|
||||
/** the state's position (within the mesh) */
|
||||
MyNavMeshLocation pos;
|
||||
|
||||
/** the state's heading */
|
||||
Heading heading;
|
||||
|
||||
MyState() : pos(), heading(0) {;}
|
||||
|
||||
MyState& operator += (const MyState& o) {
|
||||
pos.tria = nullptr; // impossible
|
||||
pos.pos += o.pos.pos;
|
||||
return *this;
|
||||
}
|
||||
|
||||
MyState& operator /= (const double val) {
|
||||
pos.tria = nullptr; // impossible
|
||||
pos.pos /= val;
|
||||
return *this;
|
||||
}
|
||||
|
||||
MyState operator * (const double val) const {
|
||||
MyState res;
|
||||
res.pos.pos = pos.pos * val;
|
||||
return res;
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
struct MyControl {
|
||||
|
||||
int numStepsSinceLastEval = 0;
|
||||
float headingChangeSinceLastEval = 0;
|
||||
|
||||
void afterEval() {
|
||||
numStepsSinceLastEval = 0;
|
||||
headingChangeSinceLastEval = 0;
|
||||
}
|
||||
|
||||
|
||||
};
|
||||
|
||||
struct MyObservation {
|
||||
|
||||
|
||||
|
||||
};
|
||||
|
||||
class MyPFInitUniform : public K::ParticleFilterInitializer<MyState> {
|
||||
|
||||
const MyNavMesh* mesh;
|
||||
|
||||
public:
|
||||
|
||||
MyPFInitUniform(const MyNavMesh* mesh) : mesh(mesh) {
|
||||
;
|
||||
}
|
||||
|
||||
virtual void initialize(std::vector<K::Particle<MyState>>& particles) override {
|
||||
|
||||
/** random position and heading within the mesh */
|
||||
Distribution::Uniform<float> dHead(0, 2*M_PI);
|
||||
MyNavMeshRandom rnd = mesh->getRandom();
|
||||
for (K::Particle<MyState>& p : particles) {
|
||||
p.state.pos = rnd.draw();
|
||||
p.state.heading = dHead.draw();
|
||||
p.weight = 1.0 / particles.size();
|
||||
}
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
class MyPFInitFixed : public K::ParticleFilterInitializer<MyState> {
|
||||
|
||||
const MyNavMesh* mesh;
|
||||
const Point3 pos;
|
||||
|
||||
public:
|
||||
|
||||
MyPFInitFixed(const MyNavMesh* mesh, const Point3 pos) : mesh(mesh), pos(pos) {
|
||||
;
|
||||
}
|
||||
|
||||
virtual void initialize(std::vector<K::Particle<MyState>>& particles) override {
|
||||
|
||||
/** random position and heading within the mesh */
|
||||
Distribution::Uniform<float> dHead(0, 2*M_PI);
|
||||
for (K::Particle<MyState>& p : particles) {
|
||||
p.state.pos = mesh->getLocation(pos);
|
||||
p.state.heading = dHead.draw();
|
||||
p.weight = 1.0 / particles.size();
|
||||
}
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
|
||||
class MyPFTrans : public K::ParticleFilterTransition<MyState, MyControl> {
|
||||
|
||||
using MyNavMeshWalk = NM::NavMeshWalkSimple<MyNavMeshTriangle>;
|
||||
MyNavMeshWalk walker;
|
||||
|
||||
public:
|
||||
|
||||
MyPFTrans(MyNavMesh& mesh) : walker(mesh) {
|
||||
|
||||
// how to evaluate drawn points
|
||||
//walker.addEvaluator(new NM::WalkEvalHeadingStartEndNormal<MyNavMeshTriangle>(0.04));
|
||||
//walker.addEvaluator(new NM::WalkEvalDistance<MyNavMeshTriangle>(0.1));
|
||||
walker.addEvaluator(new NM::WalkEvalApproachesTarget<MyNavMeshTriangle>(0.9)); // 90% for particles moving towards the target
|
||||
|
||||
}
|
||||
|
||||
void transition(std::vector<K::Particle<MyState>>& particles, const MyControl* control) override {
|
||||
|
||||
Distribution::Normal<float> dStepSizeFloor(0.70, 0.1);
|
||||
Distribution::Normal<float> dStepSizeStair(0.35, 0.1);
|
||||
Distribution::Normal<float> dHeading(0.0, 0.10);
|
||||
|
||||
|
||||
for (K::Particle<MyState>& p : particles) {
|
||||
|
||||
// how to walk
|
||||
MyNavMeshWalkParams params;
|
||||
params.heading = p.state.heading + control->headingChangeSinceLastEval + dHeading.draw();
|
||||
params.numSteps = control->numStepsSinceLastEval;
|
||||
params.start = p.state.pos;
|
||||
params.stepSizes.stepSizeFloor_m = dStepSizeFloor.draw();
|
||||
params.stepSizes.stepSizeStair_m = dStepSizeStair.draw();
|
||||
|
||||
// walk
|
||||
MyNavMeshWalk::ResultEntry res = walker.getOne(params);
|
||||
|
||||
// assign back to particle's state
|
||||
p.weight *= res.probability;
|
||||
p.state.pos = res.location;
|
||||
p.state.heading = res.heading;
|
||||
|
||||
}
|
||||
|
||||
// reset the control (0 steps, 0 delta-heading)
|
||||
//control->afterEval();
|
||||
|
||||
}
|
||||
|
||||
|
||||
};
|
||||
|
||||
class MyPFEval : public K::ParticleFilterEvaluation<MyState, MyObservation> {
|
||||
|
||||
public:
|
||||
|
||||
virtual double evaluation(std::vector<K::Particle<MyState>>& particles, const MyObservation& observation) override {
|
||||
|
||||
return 1.0;
|
||||
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
|
||||
using MyFilter = K::ParticleFilter<MyState, MyControl, MyObservation>;
|
||||
|
||||
|
||||
#endif
|
||||
94
navMesh/main.h
Normal file
94
navMesh/main.h
Normal file
@@ -0,0 +1,94 @@
|
||||
#ifndef NAV_MESH_MAIN_H
|
||||
#define NAV_MESH_MAIN_H
|
||||
|
||||
#include "mesh.h"
|
||||
#include "filter.h"
|
||||
#include <memory>
|
||||
#include <thread>
|
||||
#include <Indoor/floorplan/v2/FloorplanReader.h>
|
||||
|
||||
void navMeshMain() {
|
||||
|
||||
std::string mapFile = "/apps/paper/diss/data/maps/museum31.xml";
|
||||
|
||||
Floorplan::IndoorMap* map = Floorplan::Reader::readFromFile(mapFile);
|
||||
|
||||
NM::NavMeshSettings set;
|
||||
MyNavMesh mesh;
|
||||
MyNavMeshFactory fac(&mesh, set);
|
||||
fac.build(map);
|
||||
|
||||
const Point3 src(26, 43, 7.5);
|
||||
|
||||
// add shortest-path to destination
|
||||
//const Point3 dst(51, 45, 1.7);
|
||||
const Point3 dst(25, 45, 0);
|
||||
NM::NavMeshDijkstra::stamp<MyNavMeshTriangle>(mesh, dst);
|
||||
|
||||
// debug show
|
||||
NM::NavMeshDebug dbg;
|
||||
dbg.addMesh(mesh);
|
||||
//dbg.addDijkstra(mesh);
|
||||
dbg.draw();
|
||||
|
||||
// particle-filter
|
||||
const int numParticles = 1000;
|
||||
auto init = std::make_unique<MyPFInitFixed>(&mesh, src); // known position
|
||||
//auto init = std::make_unique<MyPFInitUniform>(&mesh); // uniform distribution
|
||||
auto eval = std::make_unique<MyPFEval>();
|
||||
auto trans = std::make_unique<MyPFTrans>(mesh);
|
||||
auto resample = std::make_unique<K::ParticleFilterResamplingSimple<MyState>>();
|
||||
auto estimate = std::make_unique<K::ParticleFilterEstimationWeightedAverage<MyState>>();
|
||||
|
||||
// setup
|
||||
MyFilter pf(numParticles, std::move(init));
|
||||
pf.setEvaluation(std::move(eval));
|
||||
pf.setTransition(std::move(trans));
|
||||
pf.setResampling(std::move(resample));
|
||||
pf.setEstimation(std::move(estimate));
|
||||
pf.setNEffThreshold(1);
|
||||
|
||||
|
||||
MyControl ctrl;
|
||||
MyObservation obs;
|
||||
|
||||
//Distribution::Uniform<float> dHead(0, 2*M_PI);
|
||||
Distribution::Normal<float> dHead(0, 0.1);
|
||||
|
||||
for (int i = 0; i < 10000; ++i) {
|
||||
|
||||
ctrl.numStepsSinceLastEval = 1;
|
||||
ctrl.headingChangeSinceLastEval = dHead.draw();
|
||||
|
||||
MyState est = pf.update(&ctrl, obs);
|
||||
|
||||
ctrl.afterEval();
|
||||
|
||||
try {
|
||||
MyNavMeshLocation loc = mesh.getLocationNearestTo(est.pos.pos);
|
||||
auto path = loc.tria->getPathToDestination<MyNavMeshTriangle>(loc.pos);
|
||||
dbg.addDijkstra(path);
|
||||
} catch (...) {;}
|
||||
|
||||
const int d = (i * 1) % 360;
|
||||
dbg.plot.getView().setCamera(60, d);
|
||||
dbg.showParticles(pf.getParticles());
|
||||
dbg.setCurPos(est.pos.pos);
|
||||
|
||||
//dbg.gp.setOutput("/tmp/123/" + std::to_string(i) + ".png");
|
||||
//dbg.gp.setTerminal("pngcairo", K::GnuplotSize(60, 30));
|
||||
|
||||
std::cout << i << std::endl;
|
||||
|
||||
dbg.draw();
|
||||
|
||||
|
||||
|
||||
std::this_thread::sleep_for(std::chrono::milliseconds(5));
|
||||
|
||||
}
|
||||
|
||||
|
||||
}
|
||||
|
||||
#endif
|
||||
32
navMesh/mesh.h
Normal file
32
navMesh/mesh.h
Normal file
@@ -0,0 +1,32 @@
|
||||
#ifndef NAV_MESH_MESH_H
|
||||
#define NAV_MESH_MESH_H
|
||||
|
||||
|
||||
#include <Indoor/navMesh/NavMesh.h>
|
||||
#include <Indoor/navMesh/NavMeshLocation.h>
|
||||
#include <Indoor/navMesh/NavMeshRandom.h>
|
||||
#include <Indoor/navMesh/NavMeshFactory.h>
|
||||
|
||||
#include <Indoor/navMesh/walk/NavMeshWalkSimple.h>
|
||||
#include <Indoor/navMesh/meta/NavMeshDijkstra.h>
|
||||
|
||||
/** the triangle to use with the nav-mesh */
|
||||
class MyNavMeshTriangle : public NM::NavMeshTriangle, public NM::NavMeshTriangleDijkstra {
|
||||
|
||||
// add own parameters here
|
||||
|
||||
public:
|
||||
|
||||
MyNavMeshTriangle(const Point3 p1, const Point3 p2, const Point3 p3, uint8_t type) : NM::NavMeshTriangle(p1, p2, p3, type) {
|
||||
;
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
using MyNavMeshFactory = NM::NavMeshFactory<MyNavMeshTriangle>;
|
||||
using MyNavMesh = NM::NavMesh<MyNavMeshTriangle>;
|
||||
using MyNavMeshLocation = NM::NavMeshLocation<MyNavMeshTriangle>;
|
||||
using MyNavMeshRandom = NM::NavMeshRandom<MyNavMeshTriangle>;
|
||||
using MyNavMeshWalkParams = NM::NavMeshWalkParams<MyNavMeshTriangle>;
|
||||
|
||||
#endif
|
||||
Reference in New Issue
Block a user