Visual Servoing Platform  version 3.6.1 under development (2024-10-13)
servoAfma6FourPoints2DCamVelocityLs_cur.cpp

Example of eye-in-hand control law. We control here a real robot, the Afma6 robot (cartesian robot, with 6 degrees of freedom). The velocity is computed in the camera frame. Visual features are the image coordinates of 4 vpDot2 points. The interaction matrix is computed using the current visual features.

/*
* ViSP, open source Visual Servoing Platform software.
* Copyright (C) 2005 - 2024 by Inria. All rights reserved.
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* This software is free software; you can redistribute it and/or modify
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* See the file LICENSE.txt at the root directory of this source
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* Edition License.
*
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*
* 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 <iostream>
#include <visp3/core/vpConfig.h>
#if defined(VISP_HAVE_AFMA6) && defined(VISP_HAVE_REALSENSE2) && defined(VISP_HAVE_DISPLAY)
#include <visp3/core/vpImage.h>
#include <visp3/core/vpIoTools.h>
#include <visp3/gui/vpDisplayFactory.h>
#include <visp3/sensor/vpRealSense2.h>
#include <visp3/blob/vpDot2.h>
#include <visp3/robot/vpRobotAfma6.h>
#include <visp3/vision/vpPose.h>
#include <visp3/visual_features/vpFeatureBuilder.h>
#include <visp3/visual_features/vpFeaturePoint.h>
#include <visp3/vs/vpServo.h>
#include <visp3/vs/vpServoDisplay.h>
// Define the object CAD model
// Here we consider 4 black blobs whose centers are located on the corners of a square.
#define L 0.06 // To deal with a 12cm by 12cm square
#ifdef ENABLE_VISP_NAMESPACE
using namespace VISP_NAMESPACE_NAME;
#endif
void compute_pose(std::vector<vpPoint> &point, const std::vector<vpDot2> &dot, const vpCameraParameters &cam,
vpHomogeneousMatrix &c_M_o, bool init)
{
vpPose pose;
for (size_t i = 0; i < point.size(); ++i) {
double x = 0, y = 0;
cog = dot[i].getCog();
vpPixelMeterConversion::convertPoint(cam, cog, x, y); // Pixel to meter conversion
point[i].set_x(x); // Perspective projection
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 camera velocities (m/s, rad/s) to achieve the task
// - the 6 measured joint velocities (m/s, rad/s)
// - the 6 measured joint positions (m, rad)
// - the 8 values of s - s*
// - the 6 values of the pose c_M_o (tx,ty,tz, rx,ry,rz) with translation
// in meters and rotations in radians
// Get the user login name
std::string username = vpIoTools::getUserName();
// Create a log filename to save velocities...
std::string 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 = logdirname + "/log.dat";
// Open the log file name
std::ofstream flog(logfilename.c_str());
try {
rs2::config config;
unsigned int width = 640, height = 480, fps = 60;
config.enable_stream(RS2_STREAM_COLOR, width, height, RS2_FORMAT_RGBA8, fps);
config.enable_stream(RS2_STREAM_DEPTH, width, height, RS2_FORMAT_Z16, fps);
config.enable_stream(RS2_STREAM_INFRARED, width, height, RS2_FORMAT_Y8, fps);
rs.open(config);
// Warm up camera
for (size_t i = 0; i < 10; ++i) {
rs.acquire(I);
}
std::shared_ptr<vpDisplay> d = vpDisplayFactory::createDisplay(I, 100, 100, "Current image");
std::cout << "-------------------------------------------------------" << std::endl;
std::cout << " Test program for vpServo " << std::endl;
std::cout << " Eye-in-hand task control, velocity computed in the camera frame" << std::endl;
std::cout << " Use of the Afma6 robot " << std::endl;
std::cout << " Interaction matrix computed with the current features " << std::endl;
std::cout << " task : servo 4 points on a square with dimension " << L << " meters" << std::endl;
std::cout << "-------------------------------------------------------" << std::endl;
std::vector<vpDot2> dot(4);
std::cout << "Click on the 4 dots clockwise starting from upper/left dot..." << std::endl;
for (size_t i = 0; i < dot.size(); ++i) {
dot[i].initTracking(I);
vpImagePoint cog = dot[i].getCog();
}
vpRobotAfma6 robot;
// Load the end-effector to camera frame transformation obtained
// using a camera intrinsic model with distortion
// Get camera intrinsics
robot.getCameraParameters(cam, I);
// Sets the current position of the visual feature
std::vector<vpFeaturePoint> s(4);
for (size_t i = 0; i < s.size(); ++i) {
vpFeatureBuilder::create(s[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
std::vector<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 c_t_o(0, 0, 0.5); // tz = 0.5 meter
vpRxyzVector c_r_o(vpMath::rad(0), vpMath::rad(0), vpMath::rad(0)); // No rotations
vpRotationMatrix c_R_o(c_r_o); // Build the rotation matrix
c_M_o.buildFrom(c_t_o, c_R_o); // Build the homogeneous matrix
// Sets the desired position of the 2D visual feature
std::vector<vpFeaturePoint> s_d(4);
// Compute the desired position of the features from the desired pose
for (size_t i = 0; i < s_d.size(); ++i) {
vpColVector cP, p;
point[i].changeFrame(c_M_o, cP);
point[i].projection(cP, p);
s_d[i].set_x(p[0]);
s_d[i].set_y(p[1]);
s_d[i].set_Z(cP[2]);
}
// Define the task
// - we want an eye-in-hand control law
// - robot is controlled in the camera frame
// - Interaction matrix is computed with the current visual features
vpServo task;
// We want to see a point on a point
for (size_t i = 0; i < s.size(); ++i) {
task.addFeature(s[i], s_d[i]);
}
// Set the proportional gain
task.setLambda(0.3);
// Display task information
task.print();
// Initialise the velocity control of the robot
std::cout << "\nHit CTRL-C to stop the loop...\n" << std::flush;
bool init_pose_from_linear_method = true;
bool quit = false;
while (!quit) {
// Acquire a new image from the camera
rs.acquire(I);
// Display this image
// For each point...
for (size_t i = 0; i < dot.size(); ++i) {
// Achieve the tracking of the dot in the image
dot[i].track(I);
}
// 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, cam, c_M_o, init_pose_from_linear_method);
if (init_pose_from_linear_method) {
init_pose_from_linear_method = false;
}
for (size_t i = 0; i < dot.size(); ++i) {
// Update the point feature from the dot location
vpFeatureBuilder::create(s[i], cam, dot[i]);
// Set the feature Z coordinate from the pose
point[i].changeFrame(c_M_o, cP);
s[i].set_Z(cP[2]);
}
// Compute the visual servoing skew vector
// Display the current and desired feature points in the image display
vpServoDisplay::display(task, cam, I);
// Apply the computed camera velocities to the robot
// 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 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() << " "; // s-s* for points
// Save the current c_M_o pose: translations in meters, rotations (rx, ry,
// rz) in radians
flog << c_t_o[0] << " " << c_t_o[1] << " " << c_t_o[2] << " " // translation
<< c_r_o[0] << " " << c_r_o[1] << " " << c_r_o[2] << std::endl; // rot
vpDisplay::displayText(I, 20, 20, "Click to quit...", vpColor::red);
if (vpDisplay::getClick(I, false)) {
quit = true;
}
// Flush the display
}
// Close the log file
flog.close();
// Display task information
task.print();
return EXIT_SUCCESS;
}
catch (const vpException &e) {
// Close the log file
flog.close();
std::cout << "Visual servo failed with exception: " << e << std::endl;
return EXIT_FAILURE;
}
}
#else
int main()
{
std::cout << "You do not have an afma6 robot connected to your computer..." << std::endl;
return EXIT_SUCCESS;
}
#endif
@ TOOL_INTEL_D435_CAMERA
Definition: vpAfma6.h:131
Generic class defining intrinsic camera parameters.
@ perspectiveProjWithDistortion
Perspective projection with distortion model.
Implementation of column vector and the associated operations.
Definition: vpColVector.h:191
static const vpColor red
Definition: vpColor.h:217
static const vpColor blue
Definition: vpColor.h:223
static bool getClick(const vpImage< unsigned char > &I, bool blocking=true)
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)
static void displayText(const vpImage< unsigned char > &I, const vpImagePoint &ip, const std::string &s, const vpColor &color)
error that can be emitted by ViSP classes.
Definition: vpException.h:60
static void create(vpFeaturePoint &s, const vpCameraParameters &cam, const vpImagePoint &t)
Implementation of an homogeneous matrix and operations on such kind of matrices.
vpHomogeneousMatrix & buildFrom(const vpTranslationVector &t, const vpRotationMatrix &R)
Class that defines a 2D point in an image. This class is useful for image processing and stores only ...
Definition: vpImagePoint.h:82
static bool checkDirectory(const std::string &dirname)
Definition: vpIoTools.cpp:396
static std::string getUserName()
Definition: vpIoTools.cpp:285
static void makeDirectory(const std::string &dirname)
Definition: vpIoTools.cpp:550
static double rad(double deg)
Definition: vpMath.h:129
static void convertPoint(const vpCameraParameters &cam, const double &u, const double &v, double &x, double &y)
Class used for pose computation from N points (pose from point only). Some of the algorithms implemen...
Definition: vpPose.h:77
void addPoint(const vpPoint &P)
Definition: vpPose.cpp:96
@ DEMENTHON_LAGRANGE_VIRTUAL_VS
Definition: vpPose.h:98
@ VIRTUAL_VS
Definition: vpPose.h:92
bool computePose(vpPoseMethodType method, vpHomogeneousMatrix &cMo, FuncCheckValidityPose func=nullptr)
Definition: vpPose.cpp:385
void acquire(vpImage< unsigned char > &grey, double *ts=nullptr)
bool open(const rs2::config &cfg=rs2::config())
Control of Irisa's gantry robot named Afma6.
Definition: vpRobotAfma6.h:212
void getVelocity(const vpRobot::vpControlFrameType frame, vpColVector &velocity)
void setVelocity(const vpRobot::vpControlFrameType frame, const vpColVector &vel) VP_OVERRIDE
@ ARTICULAR_FRAME
Definition: vpRobot.h:80
@ CAMERA_FRAME
Definition: vpRobot.h:84
@ STATE_VELOCITY_CONTROL
Initialize the velocity controller.
Definition: vpRobot.h:67
virtual vpRobotStateType setRobotState(const vpRobot::vpRobotStateType newState)
Definition: vpRobot.cpp:202
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:183
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:380
@ EYEINHAND_CAMERA
Definition: vpServo.h:161
void addFeature(vpBasicFeature &s_cur, vpBasicFeature &s_star, unsigned int select=vpBasicFeature::FEATURE_ALL)
Definition: vpServo.cpp:331
void print(const vpServo::vpServoPrintType display_level=ALL, std::ostream &os=std::cout)
Definition: vpServo.cpp:171
void setLambda(double c)
Definition: vpServo.h:986
void setServo(const vpServoType &servo_type)
Definition: vpServo.cpp:134
vpColVector getError() const
Definition: vpServo.h:510
@ PSEUDO_INVERSE
Definition: vpServo.h:235
vpColVector computeControlLaw()
Definition: vpServo.cpp:705
@ CURRENT
Definition: vpServo.h:202
Class that consider the case of a translation vector.
std::shared_ptr< vpDisplay > createDisplay()
Return a smart pointer vpDisplay specialization if a GUI library is available or nullptr otherwise.