Visual Servoing Platform version 3.5.0
testKalmanVelocity.cpp
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30 *
31 * Description:
32 * Tests some vpLinearKalmanFilterInstantiation functionalities.
33 *
34 * Authors:
35 * Fabien Spindler
36 *
37 *****************************************************************************/
38
46#include <fstream>
47#include <iostream>
48#include <visp3/core/vpLinearKalmanFilterInstantiation.h>
49
50typedef enum {
51 Position, // Considered measures are the successive positions of the target
52 Velocity // Considered measures are the successive velocities of the target
53} vpMeasureType;
54
55int main()
56{
57 try {
58 unsigned int nsignal = 2; // Number of signal to filter
59 unsigned int niter = 200;
60 unsigned int size_state_vector = 2 * nsignal;
61 unsigned int size_measure_vector = 1 * nsignal;
62 // vpMeasureType measure_t = Velocity;
63 vpMeasureType measure_t = Position;
64
65 std::string filename = "/tmp/log.dat";
66 std::ofstream flog(filename.c_str());
67
69
70 vpColVector sigma_measure(size_measure_vector);
71 for (unsigned int signal = 0; signal < nsignal; signal++)
72 sigma_measure = 0.000001;
73 vpColVector sigma_state(size_state_vector);
74
75 switch (measure_t) {
76 case Velocity:
77 for (unsigned int signal = 0; signal < nsignal; signal++) {
78 sigma_state[2 * signal] = 0.; // not used
79 sigma_state[2 * signal + 1] = 0.000001;
80 }
81 break;
82 case Position:
83 for (unsigned int signal = 0; signal < nsignal; signal++) {
84 sigma_state[2 * signal] = 0.000001;
85 sigma_state[2 * signal + 1] = 0; // not used
86 }
87 break;
88 }
89
90 vpColVector measure(size_measure_vector);
91
92 for (unsigned int signal = 0; signal < nsignal; signal++) {
93 measure[signal] = 3 + 2 * signal;
94 }
95
96 kalman.verbose(true);
97
99 double dt = 0.04; // Sampling period
100 double rho = 0.5;
101 double dummy = 0; // non used parameter
102 switch (measure_t) {
103 case Velocity:
105 kalman.setStateModel(model);
106 kalman.initFilter(nsignal, sigma_state, sigma_measure, rho, dummy);
107 break;
108 case Position:
110 kalman.setStateModel(model);
111 kalman.initFilter(nsignal, sigma_state, sigma_measure, dummy, dt);
112 break;
113 }
114
115 for (unsigned int iter = 0; iter <= niter; iter++) {
116 std::cout << "-------- iter " << iter << " ------------" << std::endl;
117 for (unsigned int signal = 0; signal < nsignal; signal++) {
118 measure[signal] = 3 + 2 * signal + 0.3 * sin(vpMath::rad(360. / niter * iter));
119 }
120 std::cout << "measure : " << measure.t() << std::endl;
121
122 flog << measure.t();
123
124 // kalman.prediction();
125 kalman.filter(measure);
126 flog << kalman.Xest.t() << std::endl;
127
128 std::cout << "Xest: " << kalman.Xest.t() << std::endl;
129 }
130
131 flog.close();
132 return 0;
133 } catch (const vpException &e) {
134 std::cout << "Catch an exception: " << e << std::endl;
135 return 1;
136 }
137}
Implementation of column vector and the associated operations.
Definition: vpColVector.h:131
vpRowVector t() const
error that can be emited by ViSP classes.
Definition: vpException.h:72
void verbose(bool on)
vpColVector Xest
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:110