Visual Servoing Platform  version 3.6.1 under development (2024-03-18)
servoViper850FourPointsKinect.cpp

Example of eye-in-hand control law. We control here a real robot, the Viper850 robot (cartesian robot, with 6 degrees of freedom). A kinect is attached to the hand. The velocity is computed in the kinect camera frame. Visual features are the image coordinates of 4 points.

/****************************************************************************
*
* ViSP, open source Visual Servoing Platform software.
* Copyright (C) 2005 - 2023 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 https://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 the camera frame
*
*****************************************************************************/
#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_LIBFREENECT_AND_DEPENDENCIES))
#include <visp3/core/vpDisplay.h>
#include <visp3/core/vpHomogeneousMatrix.h>
#include <visp3/core/vpImage.h>
#include <visp3/core/vpImageConvert.h>
#include <visp3/core/vpIoTools.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/robot/vpRobotViper850.h>
#include <visp3/sensor/vp1394TwoGrabber.h>
#include <visp3/sensor/vpKinect.h>
#include <visp3/vision/vpPose.h>
#include <visp3/visual_features/vpFeatureBuilder.h>
#include <visp3/visual_features/vpFeaturePoint.h>
#include <visp3/vs/vpServo.h>
// Exception
#include <visp3/core/vpException.h>
#include <visp3/vs/vpServoDisplay.h>
#include <visp3/blob/vpDot2.h>
#define L 0.05 // to deal with a 10cm by 10cm square
void compute_pose(vpPoint point[], vpDot2 dot[], int ndot, vpCameraParameters cam, vpHomogeneousMatrix &cMo, bool init)
{
vpPose pose;
for (int i = 0; i < ndot; i++) {
double x = 0, y = 0;
cog = dot[i].getCog();
y); // pixel to meter conversion
point[i].set_x(x); // projection perspective p
point[i].set_y(y);
pose.addPoint(point[i]);
}
if (init == true) {
} else { // init = false; use of the previous pose to initialise VIRTUAL_VS
}
}
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 8 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;
return EXIT_FAILURE;
}
}
std::string logfilename;
logfilename = logdirname + "/log.dat";
// Open the log file name
std::ofstream flog(logfilename.c_str());
try {
// Load the end-effector to camera frame transformation obtained
// using a camera intrinsic model with distortion
vpServo task;
int i;
#ifdef VISP_HAVE_LIBFREENECT_OLD
// This is the way to initialize Freenect with an old version of
// libfreenect packages under ubuntu lucid 10.04
Freenect::Freenect<vpKinect> freenect;
vpKinect &kinect = freenect.createDevice(0);
#else
Freenect::Freenect freenect;
vpKinect &kinect = freenect.createDevice<vpKinect>(0);
#endif
kinect.getRGB(Irgb);
#ifdef VISP_HAVE_X11
vpDisplayX display(I, 100, 100, "Current image");
#elif defined(HAVE_OPENCV_HIGHGUI)
vpDisplayOpenCV display(I, 100, 100, "Current image");
#elif defined(VISP_HAVE_GTK)
vpDisplayGTK display(I, 100, 100, "Current image");
#endif
std::cout << std::endl;
std::cout << "-------------------------------------------------------" << std::endl;
std::cout << " Test program for vpServo " << std::endl;
std::cout << " Eye-in-hand task control, velocity computed in the camera space" << std::endl;
std::cout << " Use of the Viper850 robot " << std::endl;
std::cout << " task : servo 4 points on a square with dimension " << L << " meters" << std::endl;
std::cout << "-------------------------------------------------------" << std::endl;
std::cout << std::endl;
vpDot2 dot[4];
std::cout << "Click on the 4 dots clockwise starting from upper/left dot..." << std::endl;
for (i = 0; i < 4; i++) {
dot[i].initTracking(I);
cog = dot[i].getCog();
}
// Get Kinect Camera Parameters
// kinect.getRGBCamParameters(cam);
robot.getCameraParameters(cam, I);
// Sets the current position of the visual feature
for (i = 0; i < 4; i++)
vpFeatureBuilder::create(p[i], cam, dot[i]); // retrieve x,y of the vpFeaturePoint structure
// Set the position of the square target in a frame which origin is
// centered in the middle of the square
vpPoint point[4];
point[0].setWorldCoordinates(-L, -L, 0);
point[1].setWorldCoordinates(L, -L, 0);
point[2].setWorldCoordinates(L, L, 0);
point[3].setWorldCoordinates(-L, L, 0);
// Initialise a desired pose to compute s*, the desired 2D point features
vpTranslationVector cto(0, 0, 0.5); // tz = 0.5 meter
vpRotationMatrix cRo(cro); // Build the rotation matrix
cMo.buildFrom(cto, cRo); // Build the homogeneous matrix
// Sets the desired position of the 2D visual feature
// Compute the desired position of the features from the desired pose
for (int i = 0; i < 4; i++) {
vpColVector cP, p;
point[i].changeFrame(cMo, cP);
point[i].projection(cP, p);
pd[i].set_x(p[0]);
pd[i].set_y(p[1]);
pd[i].set_Z(cP[2]);
}
// We want to see a point on a point
for (i = 0; i < 4; i++)
task.addFeature(p[i], pd[i]);
// Set the proportional gain
task.setLambda(0.5);
// Display task information
task.print();
// Define the task
// - we want an eye-in-hand control law
// - articular velocity are computed
task.print();
// Initialise the velocity control of the robot
std::cout << "\nHit CTRL-C to stop the loop...\n" << std::flush;
for (;;) {
// Acquire a new image from the kinect
kinect.getRGB(Irgb);
// Display this image
try {
// For each point...
for (i = 0; i < 4; i++) {
// Achieve the tracking of the dot in the image
dot[i].track(I);
// Display a green cross at the center of gravity position in the
// image
cog = dot[i].getCog();
}
} catch (...) {
flog.close(); // Close the log file
vpTRACE("Error detected while tracking visual features");
robot.stopMotion();
kinect.stop();
return EXIT_FAILURE;
}
// At first iteration, we initialise non linear pose estimation with a linear approach.
// For the other iterations, non linear pose estimation is initialized with the pose estimated at previous
// iteration of the loop
compute_pose(point, dot, 4, cam, cMo, init_pose_from_linear_method);
if (init_pose_from_linear_method) {
init_pose_from_linear_method = false;
}
for (i = 0; i < 4; i++) {
// Update the point feature from the dot location
vpFeatureBuilder::create(p[i], cam, dot[i]);
// Set the feature Z coordinate from the pose
point[i].changeFrame(cMo, cP);
p[i].set_Z(cP[2]);
}
// Compute the visual servoing skew vector
v = task.computeControlLaw();
// Display the current and desired feature points in the image display
vpServoDisplay::display(task, cam, I);
// Apply the computed joint velocities to the robot
// Save velocities applied to the robot in the log file
// v[0], v[1], v[2] correspond to joint translation velocities in m/s
// v[3], v[4], v[5] correspond to joint 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 4 feature points. For each 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;
// Flush the display
// std::cout << "|| s - s* || = " << ( task.getError() ).sumSquare() <<
// std::endl;
}
kinect.stop();
std::cout << "Display task information: " << std::endl;
task.print();
flog.close(); // Close the log file
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
Generic class defining intrinsic camera parameters.
@ perspectiveProjWithDistortion
Perspective projection with distortion model.
Implementation of column vector and the associated operations.
Definition: vpColVector.h:163
static const vpColor blue
Definition: vpColor.h:217
static const vpColor green
Definition: vpColor.h:214
The vpDisplayGTK allows to display image using the GTK 3rd party library. Thus to enable this class G...
Definition: vpDisplayGTK.h:128
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:128
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:124
void track(const vpImage< unsigned char > &I, bool canMakeTheWindowGrow=true)
Definition: vpDot2.cpp:439
vpImagePoint getCog() const
Definition: vpDot2.h:176
void initTracking(const vpImage< unsigned char > &I, unsigned int size=0)
Definition: vpDot2.cpp:245
error that can be emitted by ViSP classes.
Definition: vpException.h:59
const char * getMessage() const
Definition: vpException.cpp:64
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 set_y(double y)
void set_x(double x)
void set_Z(double Z)
Implementation of an homogeneous matrix and operations on such kind of matrices.
void buildFrom(const vpTranslationVector &t, const vpRotationMatrix &R)
static void convert(const vpImage< unsigned char > &src, vpImage< vpRGBa > &dest)
Class that defines a 2D point in an image. This class is useful for image processing and stores only ...
Definition: vpImagePoint.h:82
void init(unsigned int h, unsigned int w, Type value)
Definition: vpImage.h:623
static bool checkDirectory(const std::string &dirname)
Definition: vpIoTools.cpp:818
static std::string getUserName()
Definition: vpIoTools.cpp:711
static void makeDirectory(const std::string &dirname)
Definition: vpIoTools.cpp:967
Driver for the Kinect-1 device.
Definition: vpKinect.h:110
void stop()
Definition: vpKinect.cpp:113
void start(vpKinect::vpDMResolution res=DMAP_LOW_RES)
Definition: vpKinect.cpp:73
@ DMAP_LOW_RES
Definition: vpKinect.h:125
bool getRGB(vpImage< vpRGBa > &IRGB)
Definition: vpKinect.cpp:226
static double rad(double deg)
Definition: vpMath.h:127
static void convertPoint(const vpCameraParameters &cam, const double &u, const double &v, double &x, double &y)
Class that defines a 3D point in the object frame and allows forward projection of a 3D point in the ...
Definition: vpPoint.h:77
void set_x(double x)
Set the point x coordinate in the image plane.
Definition: vpPoint.cpp:500
void projection(const vpColVector &_cP, vpColVector &_p) const vp_override
Definition: vpPoint.cpp:223
void changeFrame(const vpHomogeneousMatrix &cMo, vpColVector &cP) const vp_override
Definition: vpPoint.cpp:240
void setWorldCoordinates(double oX, double oY, double oZ)
Definition: vpPoint.cpp:110
void set_y(double y)
Set the point y coordinate in the image plane.
Definition: vpPoint.cpp:502
Class used for pose computation from N points (pose from point only). Some of the algorithms implemen...
Definition: vpPose.h:78
void addPoint(const vpPoint &P)
Definition: vpPose.cpp:93
@ DEMENTHON_LAGRANGE_VIRTUAL_VS
Definition: vpPose.h:99
@ VIRTUAL_VS
Definition: vpPose.h:93
bool computePose(vpPoseMethodType method, vpHomogeneousMatrix &cMo, bool(*func)(const vpHomogeneousMatrix &)=nullptr)
Definition: vpPose.cpp:333
void getVelocity(const vpRobot::vpControlFrameType frame, vpColVector &velocity)
void setVelocity(const vpRobot::vpControlFrameType frame, const vpColVector &vel) vp_override
@ ARTICULAR_FRAME
Definition: vpRobot.h:78
@ CAMERA_FRAME
Definition: vpRobot.h:82
@ STATE_VELOCITY_CONTROL
Initialize the velocity controller.
Definition: vpRobot.h:65
virtual vpRobotStateType setRobotState(const vpRobot::vpRobotStateType newState)
Definition: vpRobot.cpp:198
Implementation of a rotation matrix and operations on such kind of matrices.
Implementation of a rotation vector as Euler angle minimal representation.
Definition: vpRxyzVector.h:176
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:378
@ EYEINHAND_CAMERA
Definition: vpServo.h:155
void addFeature(vpBasicFeature &s_cur, vpBasicFeature &s_star, unsigned int select=vpBasicFeature::FEATURE_ALL)
Definition: vpServo.cpp:329
void print(const vpServo::vpServoPrintType display_level=ALL, std::ostream &os=std::cout)
Definition: vpServo.cpp:169
void setLambda(double c)
Definition: vpServo.h:976
void setServo(const vpServoType &servo_type)
Definition: vpServo.cpp:132
vpColVector getError() const
Definition: vpServo.h:504
@ PSEUDO_INVERSE
Definition: vpServo.h:229
vpColVector computeControlLaw()
Definition: vpServo.cpp:703
@ CURRENT
Definition: vpServo.h:196
Class that consider the case of a translation vector.
@ TOOL_GENERIC_CAMERA
Definition: vpViper850.h:124
#define vpTRACE
Definition: vpDebug.h:405
void display(vpImage< unsigned char > &I, const std::string &title)
Display a gray-scale image.