Visual Servoing Platform
version 3.7.0
Toggle main menu visibility
Loading...
Searching...
No Matches
testKalmanVelocity.cpp
1
/*
2
* ViSP, open source Visual Servoing Platform software.
3
* Copyright (C) 2005 - 2024 by Inria. All rights reserved.
4
*
5
* This software is free software; you can redistribute it and/or modify
6
* it under the terms of the GNU General Public License as published by
7
* the Free Software Foundation; either version 2 of the License, or
8
* (at your option) any later version.
9
* See the file LICENSE.txt at the root directory of this source
10
* distribution for additional information about the GNU GPL.
11
*
12
* For using ViSP with software that can not be combined with the GNU
13
* GPL, please contact Inria about acquiring a ViSP Professional
14
* Edition License.
15
*
16
* See https://visp.inria.fr for more information.
17
*
18
* This software was developed at:
19
* Inria Rennes - Bretagne Atlantique
20
* Campus Universitaire de Beaulieu
21
* 35042 Rennes Cedex
22
* France
23
*
24
* If you have questions regarding the use of this file, please contact
25
* Inria at visp@inria.fr
26
*
27
* This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
28
* WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
29
*
30
* Description:
31
* Tests some vpLinearKalmanFilterInstantiation functionalities.
32
*/
33
40
41
#include <fstream>
42
#include <iostream>
43
#include <visp3/core/vpLinearKalmanFilterInstantiation.h>
44
45
typedef
enum
46
{
47
Position,
// Considered measures are the successive positions of the target
48
Velocity
// Considered measures are the successive velocities of the target
49
} vpMeasureType;
50
51
int
main()
52
{
53
#ifdef ENABLE_VISP_NAMESPACE
54
using namespace
VISP_NAMESPACE_NAME
;
55
#endif
56
try
{
57
unsigned
int
nsignal = 2;
// Number of signal to filter
58
unsigned
int
niter = 200;
59
unsigned
int
size_state_vector = 2 * nsignal;
60
unsigned
int
size_measure_vector = 1 * nsignal;
61
// vpMeasureType measure_t = Velocity;
62
vpMeasureType measure_t = Position;
63
64
std::string
filename
=
"/tmp/log.dat"
;
65
std::ofstream flog(
filename
.c_str());
66
67
vpLinearKalmanFilterInstantiation
kalman
;
68
69
vpColVector
sigma_measure(size_measure_vector);
70
for
(
unsigned
int
signal = 0; signal < nsignal; signal++)
71
sigma_measure = 0.000001;
72
vpColVector
sigma_state(size_state_vector);
73
74
switch
(measure_t) {
75
case
Velocity:
76
for
(
unsigned
int
signal = 0; signal < nsignal; signal++) {
77
sigma_state[2 * signal] = 0.;
// not used
78
sigma_state[2 * signal + 1] = 0.000001;
79
}
80
break
;
81
case
Position:
82
for
(
unsigned
int
signal = 0; signal < nsignal; signal++) {
83
sigma_state[2 * signal] = 0.000001;
84
sigma_state[2 * signal + 1] = 0;
// not used
85
}
86
break
;
87
}
88
89
vpColVector
measure(size_measure_vector);
90
91
for
(
unsigned
int
signal = 0; signal < nsignal; signal++) {
92
measure[signal] = 3 + 2 * signal;
93
}
94
95
kalman
.verbose(
true
);
96
97
vpLinearKalmanFilterInstantiation::vpStateModel
model;
98
double
dt
= 0.04;
// Sampling period
99
double
rho = 0.5;
100
double
dummy = 0;
// non used parameter
101
switch
(measure_t) {
102
case
Velocity:
103
model =
vpLinearKalmanFilterInstantiation::stateConstVelWithColoredNoise_MeasureVel
;
104
kalman
.setStateModel(model);
105
kalman
.initFilter(nsignal, sigma_state, sigma_measure, rho, dummy);
106
break
;
107
case
Position:
108
model =
vpLinearKalmanFilterInstantiation::stateConstVel_MeasurePos
;
109
kalman
.setStateModel(model);
110
kalman
.initFilter(nsignal, sigma_state, sigma_measure, dummy, dt);
111
break
;
112
}
113
114
for
(
unsigned
int
iter = 0;
iter
<= niter;
iter
++) {
115
std::cout <<
"-------- iter "
<<
iter
<<
" ------------"
<< std::endl;
116
for
(
unsigned
int
signal = 0; signal < nsignal; signal++) {
117
measure[signal] = 3 + 2 * signal + 0.3 * sin(
vpMath::rad
(360. / niter * iter));
118
}
119
std::cout <<
"measure : "
<< measure.t() << std::endl;
120
121
flog << measure.t();
122
123
// kalman.prediction();
124
kalman
.filter(measure);
125
flog <<
kalman
.Xest.t() << std::endl;
126
127
std::cout <<
"Xest: "
<<
kalman
.Xest.t() << std::endl;
128
}
129
130
flog.close();
131
return
EXIT_SUCCESS;
132
}
133
catch
(
const
vpException
&e) {
134
std::cout <<
"Catch an exception: "
<<
e
<< std::endl;
135
return
EXIT_FAILURE;
136
}
137
}
vpColVector
Implementation of column vector and the associated operations.
Definition
vpColVector.h:191
vpException
error that can be emitted by ViSP classes.
Definition
vpException.h:60
vpLinearKalmanFilterInstantiation
This class provides an implementation of some specific linear Kalman filters.
Definition
vpLinearKalmanFilterInstantiation.h:54
vpLinearKalmanFilterInstantiation::vpStateModel
vpStateModel
Definition
vpLinearKalmanFilterInstantiation.h:60
vpLinearKalmanFilterInstantiation::stateConstVel_MeasurePos
@ stateConstVel_MeasurePos
Definition
vpLinearKalmanFilterInstantiation.h:65
vpLinearKalmanFilterInstantiation::stateConstVelWithColoredNoise_MeasureVel
@ stateConstVelWithColoredNoise_MeasureVel
Definition
vpLinearKalmanFilterInstantiation.h:70
vpMath::rad
static double rad(double deg)
Definition
vpMath.h:129
VISP_NAMESPACE_NAME
Definition
vpEigenConversion.h:44
gen_java.filename
filename
Definition
gen_java.py:1294
ibvs-four-points.iter
int iter
Definition
ibvs-four-points.py:236
ibvs-four-points.e
e
Definition
ibvs-four-points.py:272
ukf-linear-example.dt
float dt
Definition
ukf-linear-example.py:143
yolo-centering-task-afma6.kalman
kalman
Definition
yolo-centering-task-afma6.py:249
modules
core
test
math
testKalmanVelocity.cpp
Generated by
1.17.0