tutorial_ros_node_pioneer_visual_servo.cpp

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#include <iostream>

#include <visp/vpCameraParameters.h>
#include <visp/vpDisplayX.h>
#include <visp/vpDot2.h>
#include <visp/vpFeatureBuilder.h>
#include <visp/vpFeatureDepth.h>
#include <visp/vpFeaturePoint.h>
#include <visp/vpHomogeneousMatrix.h>
#include <visp/vpImage.h>
#include <visp/vpImageConvert.h>
#include <visp/vpServo.h>
#include <visp/vpVelocityTwistMatrix.h>

#include <visp_ros/vpROSGrabber.h>
#include <visp_ros/vpROSRobotPioneer.h>

#if defined(VISP_HAVE_DC1394_2) && defined(VISP_HAVE_X11)
#  define TEST_COULD_BE_ACHIEVED
#endif


#ifdef TEST_COULD_BE_ACHIEVED
int main(int argc, char **argv)
{
  try {
    vpImage<unsigned char> I; // Create a gray level image container
    double depth = 1.;
    double lambda = 0.6;
    double coef = 1./6.77; // Scale parameter used to estimate the depth Z of the blob from its surface

    vpROSRobotPioneer robot;
    robot.setCmdVelTopic("/RosAria/cmd_vel");
    robot.init(argc, argv);

    // Wait 3 sec to be sure that the low level Aria thread used to control
    // the robot is started. Without this delay we experienced a delay (arround 2.2 sec)
    // between the velocity send to the robot and the velocity that is really applied
    // to the wheels.
    vpTime::sleepMs(3000);

    std::cout << "Robot connected" << std::endl;

    // Camera parameters. In this experiment we don't need a precise calibration of the camera
    vpCameraParameters cam;

    // Create a grabber based on libdc1394-2.x third party lib (for firewire cameras under Linux)
    vpROSGrabber g;
    g.setCameraInfoTopic("/camera/camera_info");
    g.setImageTopic("/camera/image_raw");
    g.setRectify(true);
    g.open(argc, argv);
    // Get camera parameters from /camera/camera_info topic
    if (g.getCameraInfo(cam) == false)
      cam.initPersProjWithoutDistortion(600,600,I.getWidth()/2, I.getHeight()/2);

    g.acquire(I);

    // Create an image viewer
    vpDisplayX d(I, 10, 10, "Current frame");
    vpDisplay::display(I);
    vpDisplay::flush(I);

    // Create a blob tracker
    vpDot2 dot;
    dot.setGraphics(true);
    dot.setComputeMoments(true);
    dot.setEllipsoidShapePrecision(0.);  // to track a blob without any constraint on the shape
    dot.setGrayLevelPrecision(0.9);  // to set the blob gray level bounds for binarisation
    dot.setEllipsoidBadPointsPercentage(0.5); // to be accept 50% of bad inner and outside points with bad gray level
    dot.initTracking(I);
    vpDisplay::flush(I);

    vpServo task;
    task.setServo(vpServo::EYEINHAND_L_cVe_eJe) ;
    task.setInteractionMatrixType(vpServo::DESIRED, vpServo::PSEUDO_INVERSE) ;
    task.setLambda(lambda) ;
    vpVelocityTwistMatrix cVe ;
    cVe = robot.get_cVe() ;
    task.set_cVe(cVe) ;

    std::cout << "cVe: \n" << cVe << std::endl;

    vpMatrix eJe;
    robot.get_eJe(eJe) ;
    task.set_eJe(eJe) ;
    std::cout << "eJe: \n" << eJe << std::endl;

    // Current and desired visual feature associated to the x coordinate of the point
    vpFeaturePoint s_x, s_xd;

    // Create the current x visual feature
    vpFeatureBuilder::create(s_x, cam, dot);

    // Create the desired x* visual feature
    s_xd.buildFrom(0, 0, depth);

    // Add the feature
    task.addFeature(s_x, s_xd) ;

    // Create the current log(Z/Z*) visual feature
    vpFeatureDepth s_Z, s_Zd;
    // Surface of the blob estimated from the image moment m00 and converted in meters
    double surface = 1./sqrt(dot.m00/(cam.get_px()*cam.get_py()));
    double Z, Zd;
    // Initial depth of the blob in from of the camera
    Z = coef * surface ;
    // Desired depth Z* of the blob. This depth is learned and equal to the initial depth
    Zd = Z;

    std::cout << "Z " << Z << std::endl;
    s_Z.buildFrom(s_x.get_x(), s_x.get_y(), Z , 0); // log(Z/Z*) = 0 that's why the last parameter is 0
    s_Zd.buildFrom(s_x.get_x(), s_x.get_y(), Zd , 0); // log(Z/Z*) = 0 that's why the last parameter is 0

    // Add the feature
    task.addFeature(s_Z, s_Zd) ;

    vpColVector v; // vz, wx

    while(1)
    {
      // Acquire a new image
      g.acquire(I);

      // Set the image as background of the viewer
      vpDisplay::display(I);

      // Does the blob tracking
      dot.track(I);
      // Update the current x feature
      vpFeatureBuilder::create(s_x, cam, dot);

      // Update log(Z/Z*) feature. Since the depth Z change, we need to update the intection matrix
      surface = 1./sqrt(dot.m00/(cam.get_px()*cam.get_py()));
      Z = coef * surface ;
      s_Z.buildFrom(s_x.get_x(), s_x.get_y(), Z, log(Z/Zd)) ;

      robot.get_cVe(cVe) ;
      task.set_cVe(cVe) ;

      robot.get_eJe(eJe) ;
      task.set_eJe(eJe) ;

      // Compute the control law. Velocities are computed in the mobile robot reference frame
      v = task.computeControlLaw() ;

      std::cout << "Send velocity to the pionner: " << v[0] << " m/s "
                << vpMath::deg(v[1]) << " deg/s" << std::endl;

      // Send the velocity to the robot
      robot.setVelocity(vpRobot::REFERENCE_FRAME, v);

      // Draw a vertical line which corresponds to the desired x coordinate of the dot cog
      vpDisplay::displayLine(I, 0, 320, 479, 320, vpColor::red);
      vpDisplay::flush(I);

      // A click in the viewer to exit
      if ( vpDisplay::getClick(I, false) )
        break;
    }

    std::cout << "Ending robot thread..." << std::endl;

    // Kill the servo task
    task.print() ;
    task.kill();
  }
  catch(vpException e) {
    std::cout << "Catch an exception: " << e << std::endl;
    return 1;
  }
}
#else
int main()
{
  std::cout << "You don't have the right 3rd party libraries to run this example..." << std::endl;
}
#endif