FHWS/IPIN2017
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refactoring, easy debugging

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This commit is contained in:
toni
2017-03-31 18:34:38 +02:00
parent 9b21e5627d
commit a71f082a45
4 changed files with 103 additions and 45 deletions
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2
code/Settings.h
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@@ -7,6 +7,8 @@
namespace Settings {
const bool useKLB = true;
const int numParticles = 10000;
namespace IMU {

41
code/filter/Logic.h
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@@ -14,6 +14,7 @@
#include <Indoor/grid/walk/v2/modules/WalkModuleSpread.h>
#include <Indoor/grid/walk/v2/modules/WalkModuleFavorZ.h>
#include <Indoor/grid/walk/v2/modules/WalkModulePreventVisited.h>
#include <Indoor/grid/walk/v2/modules/WalkModuleActivityControl.h>
#include <Indoor/sensors/radio/model/WiFiModelLogDistCeiling.h>
#include <Indoor/sensors/radio/WiFiProbabilityFree.h>
@@ -46,6 +47,7 @@ struct PFInit : public K::ParticleFilterInitializer<MyState> {
p.state.heading.direction = (rand() % 360) / 180.0 * M_PI; // random heading
p.state.heading.error = 0;
p.state.relativePressure = 0; // start with a relative pressure of 0
p.weight = 1.0 / particles.size(); // equal weight
}
}
@@ -75,7 +77,7 @@ struct PFInitFixed : public K::ParticleFilterInitializer<MyState> {
p.state.heading.direction = headingDeg / 180.0 * M_PI; // fixed heading
p.state.heading.error = 0;
p.state.relativePressure = 0; // start with a relative pressure of 0
p.weight = 1.0 / particles.size(); // equal weight
}
}
@@ -96,6 +98,8 @@ struct PFTrans : public K::ParticleFilterTransition<MyState, MyControl> {
WalkModuleFavorZ<MyNode, MyState> modFavorZ;
//WalkModulePreventVisited<MyNode, MyState> modPreventVisited;
//WalkModuleActivityControl<MyNode, MyState, MyControl> modActivity;
std::minstd_rand gen;
@@ -104,7 +108,7 @@ struct PFTrans : public K::ParticleFilterTransition<MyState, MyControl> {
walker.addModule(&modHead);
//walker.addModule(&modHeadMises);
//walker.addModule(&modSpread); // might help in some situations! keep in mind!
//walker.addModule(&modActivity);
//walker.addModule(&modHeadUgly);
//walker.addModule(&modImportance);
//walker.addModule(&modFavorZ);
@@ -178,18 +182,45 @@ struct PFEval : public K::ParticleFilterEvaluation<MyState, MyObs> {
return Distribution::Normal<double>::getProbability(static_cast<double>(hPa), 0.10, static_cast<double>(observation.relativePressure));
}
double getStairProb(const K::Particle<MyState>& p, const ActivityButterPressure::Activity act) {
const float kappa = 0.75;
const MyNode& gn = grid.getNodeFor(p.state.position);
switch (act) {
case ActivityButterPressure::Activity::STAY:
if (gn.getType() == GridNode::TYPE_FLOOR) {return kappa;}
if (gn.getType() == GridNode::TYPE_DOOR) {return kappa;}
{return 1-kappa;}
case ActivityButterPressure::Activity::UP:
case ActivityButterPressure::Activity::DOWN:
if (gn.getType() == GridNode::TYPE_STAIR) {return kappa;}
if (gn.getType() == GridNode::TYPE_ELEVATOR) {return kappa;}
{return 1-kappa;}
}
return 1.0;
}
virtual double evaluation(std::vector<K::Particle<MyState>>& particles, const MyObs& observation) override {
double sum = 0;
const WiFiMeasurements wifiObs = Settings::WiFiModel::vg_eval.group(observation.wifi);
for (K::Particle<MyState>& p : particles) {
#pragma omp parallel for num_threads(3)
for (int i = 0; i < Settings::numParticles; ++i) {
K::Particle<MyState>& p = particles[i];
// Point3 pos_m = p.state.position.inMeter();
// Point3 posOld_m = p.state.positionOld.inMeter();
const double pWifi = getWIFI(observation, wifiObs, p.state.position);
const double pBaroPressure = getBaroPressure(observation, p.state.relativePressure);
const double pBaroPressure = getStairProb(p, observation.activity);
//const double pBaroPressure = getBaroPressure(observation, p.state.relativePressure);
//const double pBeacon = getBEACON(observation, p.state.position);
//small checks
@@ -199,6 +230,8 @@ struct PFEval : public K::ParticleFilterEvaluation<MyState, MyObs> {
const double prob = pBaroPressure * pWifi;
p.weight = prob;
#pragma omp atomic
sum += (prob);
}

5
code/filter/Structs.h
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@@ -18,6 +18,8 @@
#include <Indoor/grid/walk/v2/modules/WalkModuleFavorZ.h>
#include <Indoor/grid/walk/v2/modules/WalkModulePreventVisited.h>
#include <Indoor/grid/walk/v2/modules/WalkModuleActivityControl.h>
struct MyState : public WalkState, public WalkStateHeading, public WalkStateSpread, public WalkStateFavorZ {
static Floorplan::IndoorMap* map;
@@ -77,6 +79,9 @@ struct MyObs {
/** wifi measurements */
WiFiMeasurements wifi;
/** detected activity */
ActivityButterPressure::Activity activity = ActivityButterPressure::Activity::STAY;
/** beacon measurements */
BeaconMeasurements beacons;

100
code/main.cpp
View File

@@ -170,11 +170,13 @@ void run(DataSetup setup, int numFile, std::string folder, std::vector<int> gtPa
pf.setEvaluation(std::unique_ptr<PFEval>(new PFEval(WiFiModel, beaconModel, grid)));
//resampling
//pf.setResampling(std::unique_ptr<K::ParticleFilterResamplingSimple<MyState>>(new K::ParticleFilterResamplingSimple<MyState>()));
//pf.setResampling(std::unique_ptr<K::ParticleFilterResamplingPercent<MyState>>(new K::ParticleFilterResamplingPercent<MyState>(0.4)));
//pf.setResampling(std::unique_ptr<NodeResampling<MyState, MyNode>>(new NodeResampling<MyState, MyNode>(*grid)););
pf.setResampling(std::unique_ptr<K::ParticleFilterResamplingDivergence<MyState>>(new K::ParticleFilterResamplingDivergence<MyState>()));
if(Settings::useKLB){
pf.setResampling(std::unique_ptr<K::ParticleFilterResamplingDivergence<MyState>>(new K::ParticleFilterResamplingDivergence<MyState>()));
} else {
//pf.setResampling(std::unique_ptr<K::ParticleFilterResamplingSimple<MyState>>(new K::ParticleFilterResamplingSimple<MyState>()));
pf.setResampling(std::unique_ptr<K::ParticleFilterResamplingPercent<MyState>>(new K::ParticleFilterResamplingPercent<MyState>(0.4)));
//pf.setResampling(std::unique_ptr<NodeResampling<MyState, MyNode>>(new NodeResampling<MyState, MyNode>(*grid)););
}
pf.setNEffThreshold(0.95);
@@ -190,6 +192,7 @@ void run(DataSetup setup, int numFile, std::string folder, std::vector<int> gtPa
StepDetection sd;
TurnDetection td;
MotionDetection md;
ActivityButterPressure act;
RelativePressure relBaro; relBaro.setCalibrationTimeframe( Timestamp::fromMS(5000) );
@@ -236,6 +239,10 @@ void run(DataSetup setup, int numFile, std::string folder, std::vector<int> gtPa
obs.relativePressure = relBaro.getPressureRealtiveToStart();
obs.sigmaPressure = relBaro.getSigma();
//activity recognition
obs.activity = act.add(ts, fr.getBarometer()[e.idx].data);
//activity for transition
} else if (e.type == Offline::Sensor::LIN_ACC) {
md.addLinearAcceleration(ts, fr.getLinearAcceleration()[e.idx].data);
@@ -249,31 +256,39 @@ void run(DataSetup setup, int numFile, std::string folder, std::vector<int> gtPa
obs.currentTime = ts;
const WiFiMeasurements wifiObs = Settings::WiFiModel::vg_eval.group(obs.wifi);
MyState est;
if(Settings::useKLB){
std::vector<MyNode> allNodes = grid.getNodes();
std::vector<K::Particle<MyState>> particleWifi;
for(MyNode node : allNodes){
double prob = wiFiProbability.getProbability(node, ts, wifiObs);
K::Particle<MyState> tmp (MyState(GridPoint(node.x_cm, node.y_cm, node.z_cm)), prob);
particleWifi.push_back(tmp);
const WiFiMeasurements wifiObs = Settings::WiFiModel::vg_eval.group(obs.wifi);
std::vector<MyNode> allNodes = grid.getNodes();
std::vector<K::Particle<MyState>> particleWifi;
for(MyNode node : allNodes){
double prob = wiFiProbability.getProbability(node, ts, wifiObs);
K::Particle<MyState> tmp (MyState(GridPoint(node.x_cm, node.y_cm, node.z_cm)), prob);
particleWifi.push_back(tmp);
}
if(kld_data.empty()){
kld_data.push_back(0.0);
}
double kld = 0.0;
//set probability distributions.
//std::function<double(std::vector<K::Particle<MyState>>&, MyState, std::vector<K::Particle<MyState>>&)> kldFunc = getKernelDensityProbability;
std::function<double(std::vector<K::Particle<MyState>>&, MyState, std::vector<K::Particle<MyState>>&)> kldFunc = kldFromMultivariatNormal;
//update filter
est = pf.update(&ctrl, obs, particleWifi, kldFunc, kld);
kld_data.push_back(kld);
} else {
est = pf.update(&ctrl, obs);
}
if(kld_data.empty()){
kld_data.push_back(0.0);
}
std::function<double(std::vector<K::Particle<MyState>>&, MyState, std::vector<K::Particle<MyState>>&)> kldFunc = getKernelDensityProbability;
//std::function<double(std::vector<K::Particle<MyState>>&, MyState, std::vector<K::Particle<MyState>>&)> kldFunc = kldFromMultivariatNormal;
double kld = 0.0;
MyState est = pf.update(&ctrl, obs, particleWifi, kldFunc, kld);
Point3 estPos = est.position.inMeter();
//double kld = getKernelDensityProbability(pf, WiFiModel, obs, grid, ts, plot);
//double kld = kldFromMultivariatNormal(pf, estPos, particleWifi, plot);
kld_data.push_back(kld);
//current ground truth position
Point3 gtPos = gtInterpolator.get(static_cast<uint64_t>(ts.ms()));
@@ -298,8 +313,10 @@ void run(DataSetup setup, int numFile, std::string folder, std::vector<int> gtPa
//plot.gp << "set label 1001 at screen 0.02, 0.98 'base:" << relBaro.getBaseAvg() << " sigma:" << relBaro.getSigma() << " cur:" << relBaro.getPressureRealtiveToStart() << " hPa " << -relBaro.getPressureRealtiveToStart()/0.10/4.0f << " floor'\n";
int minutes = static_cast<int>(ts.sec()) / 60;
plot.gp << "set label 1002 at screen 0.02, 0.94 'Time: " << minutes << ":" << static_cast<int>(static_cast<int>(ts.sec())%60) << "'\n";
plot.gp << "set label 1002 at screen 0.04, 0.94 'KLD: " << ":" << kld << "'\n";
//plot.gp << "set label 1002 at screen 0.98, 0.98 'act:" << ctrl.barometer.act << "'\n";
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 0.98, 0.98 'act:" << obs.activity << "'\n";
// error between GT and estimation
float err_m = gtPos.getDistance(estPos);
@@ -309,7 +326,6 @@ void run(DataSetup setup, int numFile, std::string folder, std::vector<int> gtPa
plot.show();
usleep(10*10);
lastTimestamp = ts;
// reset control
@@ -350,23 +366,25 @@ void run(DataSetup setup, int numFile, std::string folder, std::vector<int> gtPa
K::GnuplotPlot plotkld;
K::GnuplotPlotElementLines lines;
//save as screenshot
std::string path = "/home/toni/Documents/programme/localization/IPIN2017/code/eval/"+ folder + "/image" + std::to_string(numFile) + "_" + std::to_string(t);
gp << "set terminal png size 1280,720\n";
gp << "set output '" << path << "_shennendistance.png'\n";
//save as screenshot for klb
if(Settings::useKLB){
std::string path = "/home/toni/Documents/programme/localization/IPIN2017/code/eval/"+ folder + "/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){
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]);
K::GnuplotPoint2 p1(i, kld_data[i]);
K::GnuplotPoint2 p2(i+1, kld_data[i+1]);
lines.addSegment(p1, p2);
lines.addSegment(p1, p2);
}
plotkld.add(&lines);
gp.draw(plotkld);
gp.flush();
}
plotkld.add(&lines);
gp.draw(plotkld);
gp.flush();
std::cout << "finished" << std::endl;
sleep(1);
@@ -380,7 +398,7 @@ int main(int argc, char** argv) {
//for(int i = 0; i < 5; ++i){
//run(data.IPIN2017, 0, "ipin2017"); // Nexus Path2
//run(data.IPIN2017, 1, "ipin2017");
run(data.IPIN2017, 4, "ipin2017", Settings::Paths_IPIN2017::path3);
//run(data.IPIN2017, 4, "ipin2017", Settings::Paths_IPIN2017::path3);
run(data.IPIN2017, 2, "ipin2017", Settings::Paths_IPIN2017::path2);
run(data.IPIN2017, 5, "ipin2017", Settings::Paths_IPIN2017::path3);
run(data.IPIN2017, 3, "ipin2017", Settings::Paths_IPIN2017::path2);