251 lines
7.7 KiB
C++
251 lines
7.7 KiB
C++
#ifndef FILTER_H
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#define FILTER_H
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#include <KLib/math/filter/particles/ParticleFilter.h>
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#include <KLib/math/filter/particles/estimation/ParticleFilterEstimationWeightedAverage.h>
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#include <KLib/math/filter/particles/estimation/ParticleFilterEstimationOrderedWeightedAverage.h>
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#include <KLib/math/filter/particles/resampling/ParticleFilterResamplingSimple.h>
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#include <KLib/math/filter/particles/resampling/ParticleFilterResamplingPercent.h>
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#include <Indoor/sensors/radio/WiFiProbabilityFree.h>
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#include <Indoor/sensors/radio/model/WiFiModelLogDistCeiling.h>
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#include <Indoor/sensors/radio/WiFiProbabilityFree.h>
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#include <Indoor/sensors/radio/WiFiProbabilityGrid.h>
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#include <Indoor/grid/walk/v2/modules/WalkModuleHeadingControl.h>
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#include <Indoor/grid/walk/v2/modules/WalkModuleNodeImportance.h>
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#include <Indoor/grid/walk/v2/modules/WalkModuleFavorZ.h>
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#include <Indoor/grid/walk/v2/modules/WalkModuleActivityControl.h>
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#include <Indoor/grid/walk/v2/modules/WalkModuleFollowDestination.h>
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#include "State.h"
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#include "Node.h"
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#include "NodeResampling.h"
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#include "../Settings.h"
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#include <omp.h>
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#include <future>
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class PFInit : public K::ParticleFilterInitializer<MyState> {
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private:
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Grid<MyGridNode>* grid;
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public:
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PFInit(Grid<MyGridNode>* grid) : grid(grid) {
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}
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virtual void initialize(std::vector<K::Particle<MyState>>& particles) override {
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std::minstd_rand gen;
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std::uniform_int_distribution<int> distIdx(0, grid->getNumNodes()-1);
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std::uniform_real_distribution<float> distHead(0, 2*M_PI);
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for (K::Particle<MyState>& p : particles) {
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const int idx = distIdx(gen);
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const MyGridNode& node = (*grid)[idx];
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p.state.position = node; // random position
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p.state.heading.direction = Heading(distHead(gen)); // random heading
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p.weight = 1.0 / particles.size(); // equal weight
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}
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// // fix position + heading
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// for (K::Particle<MyState>& p : particles) {
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//// const int idx = 9000;
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//// const MyGridNode& node = (*grid)[idx];
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// const MyGridNode& node = grid->getNodeFor(GridPoint(2000, 2000, 0)); // center of the testmap
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// p.state.position = node;
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// p.state.heading.direction = Heading(0);
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// }
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}
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};
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class PFTrans : public K::ParticleFilterTransition<MyState, MyControl> {
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public:
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/** local, static control-data COPY */
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MyControl ctrl;
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Grid<MyGridNode>* grid;
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GridWalker<MyGridNode, MyState> walker;
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WalkModuleFavorZ<MyGridNode, MyState> modFavorZ;
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WalkModuleHeadingControl<MyGridNode, MyState, MyControl> modHeading;
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WalkModuleNodeImportance<MyGridNode, MyState> modImportance;
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WalkModuleFollowDestination<MyGridNode, MyState> modDestination;
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WalkModuleActivityControl<MyGridNode, MyState, MyControl> modActivity;
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NodeResampling<MyState, MyGridNode> resampler;
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std::minstd_rand gen;
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public:
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PFTrans(Grid<MyGridNode>* grid) : grid(grid), modHeading(&ctrl, Settings::IMU::turnSigma), modDestination(*grid), modActivity(&ctrl), resampler(*grid) {
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//walker.addModule(&modFavorZ);
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walker.addModule(&modHeading);
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//walker.addModule(&modImportance);
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walker.addModule(&modActivity);
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if (Settings::destination != GridPoint(0,0,0)) {
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//walker.addModule(&modDestination);
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modDestination.setDestination(grid->getNodeFor(Settings::destination));
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}
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}
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void transition(std::vector<K::Particle<MyState>>& particles, const MyControl* _ctrl) override {
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// local copy!! observation might be changed async outside!! (will really produces crashes!)
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this->ctrl = *_ctrl;
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((MyControl*)_ctrl)->resetAfterTransition();
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std::normal_distribution<float> noise(0, Settings::IMU::stepSigma);
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// sanity check
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Assert::equal((int)particles.size(), Settings::numParticles, "number of particles does not match the settings!");
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//for (K::Particle<MyState>& p : particles) {
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#pragma omp parallel for num_threads(3)
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for (int i = 0; i < Settings::numParticles; ++i) {
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//#pragma omp atomic
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const float dist_m = std::abs(ctrl.numStepsSinceLastTransition * Settings::IMU::stepLength + noise(gen));
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K::Particle<MyState>& p = particles[i];
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double prob;
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p.state = walker.getDestination(*grid, p.state, dist_m, prob);
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//p.weight *= prob;//(prob > 0.01) ? (1.0) : (0.15);
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//p.weight = (prob > 0.01) ? (1.0) : (0.15);
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//p.weight = prob;
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//p.weight = 1.0; // reset
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//p.weight = std::pow(p.weight, 0.1); // make all particles a little more equal [less strict]
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//p.weight *= std::pow(prob, 0.1); // add grid-walk-probability
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p.weight = prob; // grid-walk-probability
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if (p.weight != p.weight) {throw Exception("nan");}
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}
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}
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};
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class PFEval : public K::ParticleFilterEvaluation<MyState, MyObservation> {
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Grid<MyGridNode>* grid;
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WiFiModelLogDistCeiling& wifiModel;
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//WiFiObserverFree wiFiProbability; // free-calculation
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WiFiObserverGrid<MyGridNode> wiFiProbability; // grid-calculation
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// how to perform VAP grouping. also see calibration in Controller.cpp
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VAPGrouper vg = VAPGrouper(VAPGrouper::Mode::LAST_MAC_DIGIT_TO_ZERO, VAPGrouper::Aggregation::AVERAGE);
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// smartphone is 1.3 meter above ground
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const Point3 person = Point3(0,0,Settings::smartphoneAboveGround);
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public:
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PFEval(Grid<MyGridNode>* grid, WiFiModelLogDistCeiling& wifiModel) :
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grid(grid), wifiModel(wifiModel),
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//wiFiProbability(Settings::WiFiModel::sigma, wifiModel) { // WiFi free
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wiFiProbability(Settings::WiFiModel::sigma) { // WiFi grid
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}
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double getStairProb(const K::Particle<MyState>& p, const ActivityButterPressure::Activity act) {
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const float kappa = 0.75;
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const MyGridNode& gn = grid->getNodeFor(p.state.position);
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switch (act) {
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case ActivityButterPressure::Activity::STAY:
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if (gn.getType() == GridNode::TYPE_FLOOR) {return kappa;}
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if (gn.getType() == GridNode::TYPE_DOOR) {return kappa;}
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{return 1-kappa;}
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case ActivityButterPressure::Activity::UP:
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case ActivityButterPressure::Activity::DOWN:
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if (gn.getType() == GridNode::TYPE_STAIR) {return kappa;}
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if (gn.getType() == GridNode::TYPE_ELEVATOR) {return kappa;}
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{return 1-kappa;}
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}
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return 1.0;
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}
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double evaluation(std::vector<K::Particle<MyState>>& particles, const MyObservation& _observation) override {
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double sum = 0;
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// local copy!! observation might be changed async outside!! (will really produces crashes!)
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const MyObservation observation = _observation;
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// vap-grouping
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const int numAP1 = observation.wifi.entries.size();
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const WiFiMeasurements wifiObs = vg.group(_observation.wifi);
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const int numAP2 = wifiObs.entries.size();
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Log::add("Filter", "VAP: " + std::to_string(numAP1) + " -> " + std::to_string(numAP2));
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// sanity check
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Assert::equal((int)particles.size(), Settings::numParticles, "number of particles does not match the settings!");
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#pragma omp parallel for num_threads(3)
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for (int i = 0; i < Settings::numParticles; ++i) {
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K::Particle<MyState>& p = particles[i];
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// WiFi free
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//const double pWiFi = wiFiProbability.getProbability(p.state.position.inMeter()+person, observation.currentTime, vg.group(observation.wifi));
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// WiFi grid
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const MyGridNode& node = grid->getNodeFor(p.state.position);
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const double pWiFi = wiFiProbability.getProbability(node, observation.currentTime, wifiObs);
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//Log::add("xxx", std::to_string(observation.currentTime.ms()) + "_" + std::to_string(wifiObs.entries[0].ts.ms()));
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const double pStair = getStairProb(p, observation.activity);
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const double pGPS = 1;
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const double prob = pWiFi * pGPS * pStair;
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p.weight *= prob; // NOTE: keeps the weight returned by the transition step!
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//p.weight = prob; // does NOT keep the weights returned by the transition step
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if (p.weight != p.weight) {throw Exception("nan");}
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#pragma omp atomic
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sum += p.weight;
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}
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return sum;
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}
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};
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#endif // FILTER_H
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