Visual Servoing Platform  version 3.6.1 under development (2024-02-13)
testKalmanAcceleration.cpp
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31  * Description:
32  * Tests some vpLinearKalmanFilterInstantiation functionalities.
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34 *****************************************************************************/
35 
43 #include <fstream>
44 #include <iostream>
45 #include <visp3/core/vpLinearKalmanFilterInstantiation.h>
46 
47 int main()
48 {
49  try {
50  unsigned int nsignal = 1; // Number of signal to filter
51  unsigned int niter = 100;
52 
53  std::string filename = "/tmp/log.dat";
54  std::ofstream flog(filename.c_str());
55 
57 
60  kalman.setStateModel(model);
61 
62  unsigned int size_state_vector = kalman.getStateSize() * nsignal;
63  unsigned int size_measure_vector = kalman.getMeasureSize() * nsignal;
64 
65  vpColVector sigma_measure(size_measure_vector);
66  for (unsigned int signal = 0; signal < nsignal; signal++)
67  sigma_measure = 0.0001;
68  vpColVector sigma_state(size_state_vector);
69  for (unsigned int signal = 0; signal < nsignal; signal++) {
70  sigma_state[3 * signal] = 0.; // not used
71  sigma_state[3 * signal + 1] = 0.000001;
72  sigma_state[3 * signal + 2] = 0.000001;
73  }
74 
75  vpColVector velocity_measure(size_measure_vector);
76 
77  double rho = 0.9; // correlation
78  double dt = 0.2; // sampling period
79 
80  for (unsigned int signal = 0; signal < nsignal; signal++)
81  velocity_measure[signal] = 3 + 2 * signal;
82 
83  kalman.verbose(false);
84  kalman.initFilter(nsignal, sigma_state, sigma_measure, rho, dt);
85 
86  for (unsigned int iter = 0; iter <= niter; iter++) {
87  std::cout << "-------- iter " << iter << " ------------" << std::endl;
88  for (unsigned int signal = 0; signal < nsignal; signal++) {
89  velocity_measure[signal] = 3 + 2 * signal + 0.3 * sin(vpMath::rad(360. / niter * iter));
90  }
91  std::cout << "measure : " << velocity_measure.t() << std::endl;
92 
93  flog << velocity_measure.t();
94 
95  // kalman.prediction();
96  kalman.filter(velocity_measure);
97  flog << kalman.Xest.t();
98  flog << kalman.Xpre.t();
99 
100  std::cout << "Xest: " << kalman.Xest.t() << std::endl;
101  std::cout << "Xpre: " << kalman.Xpre.t() << std::endl;
102 
103  flog << std::endl;
104  }
105 
106  flog.close();
107  return EXIT_SUCCESS;
108  } catch (const vpException &e) {
109  std::cout << "Catch an exception: " << e << std::endl;
110  return EXIT_FAILURE;
111  }
112 }
Implementation of column vector and the associated operations.
Definition: vpColVector.h:163
vpRowVector t() const
error that can be emitted by ViSP classes.
Definition: vpException.h:59
vpColVector Xpre
unsigned int getMeasureSize()
void verbose(bool on)
vpColVector Xest
unsigned int getStateSize()
This class provides an implementation of some specific linear Kalman filters.
void initFilter(unsigned int nsignal, vpColVector &sigma_state, vpColVector &sigma_measure, double rho, double dt)
static double rad(double deg)
Definition: vpMath.h:127