Visual Servoing Platform  version 3.5.1 under development (2022-12-02)
servoViper850Point2DCamVelocityKalman.cpp

Example of eye-in-hand control law. We control here a real robot, the ADEPT Viper 850 robot (arm, with 6 degrees of freedom). The velocity is computed in the camera frame. The visual feature is the center of gravity of a point. We use here a linear Kalman filter with a constant velocity state model to estimate the moving target motion.

/****************************************************************************
*
* ViSP, open source Visual Servoing Platform software.
* Copyright (C) 2005 - 2019 by Inria. All rights reserved.
*
* This software is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
* See the file LICENSE.txt at the root directory of this source
* distribution for additional information about the GNU GPL.
*
* For using ViSP with software that can not be combined with the GNU
* GPL, please contact Inria about acquiring a ViSP Professional
* Edition License.
*
* See http://visp.inria.fr for more information.
*
* This software was developed at:
* Inria Rennes - Bretagne Atlantique
* Campus Universitaire de Beaulieu
* 35042 Rennes Cedex
* France
*
* If you have questions regarding the use of this file, please contact
* Inria at visp@inria.fr
*
* This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
* WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
*
* Description:
* tests the control law
* eye-in-hand control
* velocity computed in camera frame
*
* Authors:
* Eric Marchand
* Fabien Spindler
*
*****************************************************************************/
#include <visp3/core/vpConfig.h>
#include <visp3/core/vpDebug.h> // Debug trace
#include <fstream>
#include <iostream>
#include <sstream>
#include <stdio.h>
#include <stdlib.h>
#if (defined(VISP_HAVE_VIPER850) && defined(VISP_HAVE_DC1394))
#include <visp3/blob/vpDot2.h>
#include <visp3/core/vpDisplay.h>
#include <visp3/core/vpException.h>
#include <visp3/core/vpHomogeneousMatrix.h>
#include <visp3/core/vpImage.h>
#include <visp3/core/vpIoTools.h>
#include <visp3/core/vpLinearKalmanFilterInstantiation.h>
#include <visp3/core/vpMath.h>
#include <visp3/core/vpPoint.h>
#include <visp3/gui/vpDisplayGTK.h>
#include <visp3/gui/vpDisplayOpenCV.h>
#include <visp3/gui/vpDisplayX.h>
#include <visp3/io/vpImageIo.h>
#include <visp3/robot/vpRobotViper850.h>
#include <visp3/sensor/vp1394TwoGrabber.h>
#include <visp3/visual_features/vpFeatureBuilder.h>
#include <visp3/visual_features/vpFeaturePoint.h>
#include <visp3/vs/vpAdaptiveGain.h>
#include <visp3/vs/vpServo.h>
#include <visp3/vs/vpServoDisplay.h>
int main()
{
// Log file creation in /tmp/$USERNAME/log.dat
// This file contains by line:
// - the 6 computed joint velocities (m/s, rad/s) to achieve the task
// - the 6 mesured joint velocities (m/s, rad/s)
// - the 6 mesured joint positions (m, rad)
// - the 2 values of s - s*
std::string username;
// Get the user login name
// Create a log filename to save velocities...
std::string logdirname;
logdirname = "/tmp/" + username;
// Test if the output path exist. If no try to create it
if (vpIoTools::checkDirectory(logdirname) == false) {
try {
// Create the dirname
} catch (...) {
std::cerr << std::endl << "ERROR:" << std::endl;
std::cerr << " Cannot create " << logdirname << std::endl;
exit(-1);
}
}
std::string logfilename;
logfilename = logdirname + "/log.dat";
// Open the log file name
std::ofstream flog(logfilename.c_str());
vpServo task;
try {
// Initialize linear Kalman filter
// Initialize the kalman filter
unsigned int nsignal = 2; // The two values of dedt
double rho = 0.3;
vpColVector sigma_state;
vpColVector sigma_measure(nsignal);
unsigned int state_size = 0; // Kalman state vector size
state_size = kalman.getStateSize();
sigma_state.resize(state_size * nsignal);
sigma_state = 0.00001; // Same state variance for all signals
sigma_measure = 0.05; // Same measure variance for all the signals
double dummy = 0; // non used parameter dt for the velocity state model
kalman.initFilter(nsignal, sigma_state, sigma_measure, rho, dummy);
// Initialize the robot
bool reset = false;
vp1394TwoGrabber g(reset);
#if 1
#else
#endif
g.open(I);
double Tloop = 1. / 80.f;
g.getFramerate(fps);
switch (fps) {
Tloop = 1.f / 15.f;
break;
Tloop = 1.f / 30.f;
break;
Tloop = 1.f / 60.f;
break;
Tloop = 1.f / 120.f;
break;
default:
break;
}
#ifdef VISP_HAVE_X11
vpDisplayX display(I, (int)(100 + I.getWidth() + 30), 200, "Current image");
#elif defined(VISP_HAVE_OPENCV)
vpDisplayOpenCV display(I, (int)(100 + I.getWidth() + 30), 200, "Current image");
#elif defined(VISP_HAVE_GTK)
vpDisplayGTK display(I, (int)(100 + I.getWidth() + 30), 200, "Current image");
#endif
vpDot2 dot;
dot.setGraphics(true);
for (int i = 0; i < 10; i++)
g.acquire(I);
std::cout << "Click on a dot..." << std::endl;
dot.initTracking(I);
cog = dot.getCog();
// Update camera parameters
robot.getCameraParameters(cam, I);
// sets the current position of the visual feature
// retrieve x,y and Z of the vpPoint structure
// sets the desired position of the visual feature
pd.buildFrom(0, 0, 1);
// define the task
// - we want an eye-in-hand control law
// - robot is controlled in the camera frame
// - we want to see a point on a point
task.addFeature(p, pd);
// - set the constant gain
lambda.initStandard(4, 0.2, 30);
task.setLambda(lambda);
// Display task information
task.print();
// Now the robot will be controlled in velocity
std::cout << "\nHit CTRL-C to stop the loop...\n" << std::flush;
vpColVector v, v1, v2;
int iter = 0;
vpColVector vm(6);
double t_0, t_1, Tv;
vpColVector err(2), err_1(2);
vpColVector dedt_filt(2), dedt_mes(2);
dc1394video_frame_t *frame = NULL;
for (;;) {
try {
t_0 = vpTime::measureTimeMs(); // t_0: current time
// Update loop time in second
Tv = (double)(t_0 - t_1) / 1000.0;
// Update time for next iteration
t_1 = t_0;
// Acquire a new image from the camera
frame = g.dequeue(I);
// Display this image
// Achieve the tracking of the dot in the image
dot.track(I);
// Get the dot cog
cog = dot.getCog();
// Display a green cross at the center of gravity position in the
// image
// Update the point feature from the dot location
// Compute the visual servoing skew vector
v1 = task.computeControlLaw();
// Get the error ||s-s*||
err = task.getError();
if (iter == 0) {
err_1 = 0;
dedt_mes = 0;
} else {
dedt_mes = (err - err_1) / (Tv)-J1 * vm;
err_1 = err;
}
// Filter de/dt
if (iter < 2)
dedt_mes = 0;
kalman.filter(dedt_mes);
// Get the filtered values
for (unsigned int i = 0; i < nsignal; i++) {
dedt_filt[i] = kalman.Xest[i * state_size];
}
if (iter < 2)
dedt_filt = 0;
v2 = -J1p * dedt_filt;
// Update the robot camera velocity
v = v1 + v2;
// Display the current and desired feature points in the image display
vpServoDisplay::display(task, cam, I);
// Apply the computed camera velocities to the robot
iter++;
// Synchronize the loop with the image frame rate
vpTime::wait(t_0, 1000. * Tloop);
// Release the ring buffer used for the last image to start a new acq
g.enqueue(frame);
} catch (...) {
std::cout << "Tracking failed... Stop the robot." << std::endl;
v = 0;
// Stop robot
return 0;
}
// Save velocities applied to the robot in the log file
// v[0], v[1], v[2] correspond to camera translation velocities in m/s
// v[3], v[4], v[5] correspond to camera rotation velocities in rad/s
flog << v[0] << " " << v[1] << " " << v[2] << " " << v[3] << " " << v[4] << " " << v[5] << " ";
// Get the measured joint velocities of the robot
// Save measured joint velocities of the robot in the log file:
// - qvel[0], qvel[1], qvel[2] correspond to measured joint translation
// velocities in m/s
// - qvel[3], qvel[4], qvel[5] correspond to measured joint rotation
// velocities in rad/s
flog << qvel[0] << " " << qvel[1] << " " << qvel[2] << " " << qvel[3] << " " << qvel[4] << " " << qvel[5] << " ";
// Get the measured joint positions of the robot
robot.getPosition(vpRobot::ARTICULAR_FRAME, q);
// Save measured joint positions of the robot in the log file
// - q[0], q[1], q[2] correspond to measured joint translation
// positions in m
// - q[3], q[4], q[5] correspond to measured joint rotation
// positions in rad
flog << q[0] << " " << q[1] << " " << q[2] << " " << q[3] << " " << q[4] << " " << q[5] << " ";
// Save feature error (s-s*) for the feature point. For this feature
// point, we have 2 errors (along x and y axis). This error is
// expressed in meters in the camera frame
flog << (task.getError()).t() << std::endl; // s-s* for point
// Flush the display
}
flog.close(); // Close the log file
// Display task information
task.print();
return EXIT_SUCCESS;
} catch (const vpException &e) {
flog.close(); // Close the log file
std::cout << "Catch an exception: " << e.getMessage() << std::endl;
return EXIT_FAILURE;
}
}
#else
int main()
{
std::cout << "You do not have an Viper 850 robot connected to your computer..." << std::endl;
return EXIT_SUCCESS;
}
#endif
Class for firewire ieee1394 video devices using libdc1394-2.x api.
void getFramerate(vp1394TwoFramerateType &fps)
void acquire(vpImage< unsigned char > &I)
void setColorCoding(vp1394TwoColorCodingType coding)
void setVideoMode(vp1394TwoVideoModeType videomode)
void enqueue(dc1394video_frame_t *frame)
void setFramerate(vp1394TwoFramerateType fps)
dc1394video_frame_t * dequeue()
void open(vpImage< unsigned char > &I)
Adaptive gain computation.
void initStandard(double gain_at_zero, double gain_at_infinity, double slope_at_zero)
Generic class defining intrinsic camera parameters.
Implementation of column vector and the associated operations.
Definition: vpColVector.h:131
void resize(unsigned int i, bool flagNullify=true)
Definition: vpColVector.h:314
static const vpColor blue
Definition: vpColor.h:223
static const vpColor green
Definition: vpColor.h:220
The vpDisplayGTK allows to display image using the GTK 3rd party library. Thus to enable this class G...
Definition: vpDisplayGTK.h:135
The vpDisplayOpenCV allows to display image using the OpenCV library. Thus to enable this class OpenC...
Use the X11 console to display images on unix-like OS. Thus to enable this class X11 should be instal...
Definition: vpDisplayX.h:135
static void display(const vpImage< unsigned char > &I)
static void displayCross(const vpImage< unsigned char > &I, const vpImagePoint &ip, unsigned int size, const vpColor &color, unsigned int thickness=1)
static void flush(const vpImage< unsigned char > &I)
This tracker is meant to track a blob (connex pixels with same gray level) on a vpImage.
Definition: vpDot2.h:127
void track(const vpImage< unsigned char > &I, bool canMakeTheWindowGrow=true)
Definition: vpDot2.cpp:442
void setGraphics(bool activate)
Definition: vpDot2.h:314
vpImagePoint getCog() const
Definition: vpDot2.h:180
void initTracking(const vpImage< unsigned char > &I, unsigned int size=0)
Definition: vpDot2.cpp:253
error that can be emited by ViSP classes.
Definition: vpException.h:72
const char * getMessage() const
Definition: vpException.cpp:87
static void create(vpFeaturePoint &s, const vpCameraParameters &cam, const vpDot &d)
Class that defines a 2D point visual feature which is composed by two parameters that are the cartes...
void buildFrom(double x, double y, double Z)
Class that defines a 2D point in an image. This class is useful for image processing and stores only ...
Definition: vpImagePoint.h:89
unsigned int getWidth() const
Definition: vpImage.h:246
static bool checkDirectory(const std::string &dirname)
Definition: vpIoTools.cpp:431
static std::string getUserName()
Definition: vpIoTools.cpp:327
static void makeDirectory(const std::string &dirname)
Definition: vpIoTools.cpp:581
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)
Implementation of a matrix and operations on matrices.
Definition: vpMatrix.h:154
void setVelocity(const vpRobot::vpControlFrameType frame, const vpColVector &vel)
void getVelocity(const vpRobot::vpControlFrameType frame, vpColVector &velocity)
@ ARTICULAR_FRAME
Definition: vpRobot.h:79
@ CAMERA_FRAME
Definition: vpRobot.h:83
@ STATE_VELOCITY_CONTROL
Initialize the velocity controller.
Definition: vpRobot.h:67
virtual vpRobotStateType setRobotState(const vpRobot::vpRobotStateType newState)
Definition: vpRobot.cpp:201
static void display(const vpServo &s, const vpCameraParameters &cam, const vpImage< unsigned char > &I, vpColor currentColor=vpColor::green, vpColor desiredColor=vpColor::red, unsigned int thickness=1)
void setInteractionMatrixType(const vpServoIteractionMatrixType &interactionMatrixType, const vpServoInversionType &interactionMatrixInversion=PSEUDO_INVERSE)
Definition: vpServo.cpp:564
@ EYEINHAND_CAMERA
Definition: vpServo.h:155
void print(const vpServo::vpServoPrintType display_level=ALL, std::ostream &os=std::cout)
Definition: vpServo.cpp:303
void setLambda(double c)
Definition: vpServo.h:404
void setServo(const vpServoType &servo_type)
Definition: vpServo.cpp:215
vpMatrix getTaskJacobian() const
Definition: vpServo.cpp:1752
vpColVector getError() const
Definition: vpServo.h:278
@ PSEUDO_INVERSE
Definition: vpServo.h:202
vpColVector computeControlLaw()
Definition: vpServo.cpp:926
vpMatrix getTaskJacobianPseudoInverse() const
Definition: vpServo.cpp:1772
@ DESIRED
Definition: vpServo.h:186
void addFeature(vpBasicFeature &s, vpBasicFeature &s_star, unsigned int select=vpBasicFeature::FEATURE_ALL)
Definition: vpServo.cpp:487
VISP_EXPORT int wait(double t0, double t)
VISP_EXPORT double measureTimeMs()