Visual Servoing Platform  version 3.5.1 under development (2022-10-03)
servoFrankaIBVS.cpp

Example of eye-in-hand image-based control law. We control here a real robot, the Franka Emika Panda robot (arm with 7 degrees of freedom). The velocity is computed in the camera frame. The inverse jacobian that converts cartesian velocities in joint velocities is implemented in the robot low level controller. Visual features are the image coordinates of 4 points corresponding to the corners of an AprilTag.

The device used to acquire images is a Realsense D435 device.

Camera extrinsic (eMc) parameters are set by default to a value that will not match Your configuration. Use –eMc command line option to read the values from a file. This file could be obtained following extrinsic camera calibration tutorial: https://visp-doc.inria.fr/doxygen/visp-daily/tutorial-calibration-extrinsic.html

Camera intrinsic parameters are retrieved from the Realsense SDK.

The target is an AprilTag that is by default 12cm large. To print your own tag, see https://visp-doc.inria.fr/doxygen/visp-daily/tutorial-detection-apriltag.html You can specify the size of your tag using –tag_size command line option.

/****************************************************************************
*
* ViSP, open source Visual Servoing Platform software.
* Copyright (C) 2005 - 2022 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 the camera frame
*
* Authors:
* Fabien Spindler
*
*****************************************************************************/
#include <iostream>
#include <visp3/core/vpCameraParameters.h>
#include <visp3/detection/vpDetectorAprilTag.h>
#include <visp3/gui/vpDisplayGDI.h>
#include <visp3/gui/vpDisplayX.h>
#include <visp3/gui/vpPlot.h>
#include <visp3/io/vpImageIo.h>
#include <visp3/robot/vpRobotFranka.h>
#include <visp3/sensor/vpRealSense2.h>
#include <visp3/visual_features/vpFeatureBuilder.h>
#include <visp3/visual_features/vpFeaturePoint.h>
#include <visp3/vs/vpServo.h>
#include <visp3/vs/vpServoDisplay.h>
#if defined(VISP_HAVE_REALSENSE2) && (VISP_CXX_STANDARD >= VISP_CXX_STANDARD_11) && \
(defined(VISP_HAVE_X11) || defined(VISP_HAVE_GDI)) && defined(VISP_HAVE_FRANKA)
void display_point_trajectory(const vpImage<unsigned char> &I, const std::vector<vpImagePoint> &vip,
std::vector<vpImagePoint> *traj_vip)
{
for (size_t i = 0; i < vip.size(); i++) {
if (traj_vip[i].size()) {
// Add the point only if distance with the previous > 1 pixel
if (vpImagePoint::distance(vip[i], traj_vip[i].back()) > 1.) {
traj_vip[i].push_back(vip[i]);
}
} else {
traj_vip[i].push_back(vip[i]);
}
}
for (size_t i = 0; i < vip.size(); i++) {
for (size_t j = 1; j < traj_vip[i].size(); j++) {
vpDisplay::displayLine(I, traj_vip[i][j - 1], traj_vip[i][j], vpColor::green, 2);
}
}
}
int main(int argc, char **argv)
{
double opt_tagSize = 0.120;
std::string opt_robot_ip = "192.168.1.1";
std::string opt_eMc_filename = "";
bool display_tag = true;
int opt_quad_decimate = 2;
bool opt_verbose = false;
bool opt_plot = false;
bool opt_adaptive_gain = false;
bool opt_task_sequencing = false;
double convergence_threshold = 0.00005;
for (int i = 1; i < argc; i++) {
if (std::string(argv[i]) == "--tag_size" && i + 1 < argc) {
opt_tagSize = std::stod(argv[i + 1]);
} else if (std::string(argv[i]) == "--ip" && i + 1 < argc) {
opt_robot_ip = std::string(argv[i + 1]);
} else if (std::string(argv[i]) == "--eMc" && i + 1 < argc) {
opt_eMc_filename = std::string(argv[i + 1]);
} else if (std::string(argv[i]) == "--verbose") {
opt_verbose = true;
} else if (std::string(argv[i]) == "--plot") {
opt_plot = true;
} else if (std::string(argv[i]) == "--adaptive_gain") {
opt_adaptive_gain = true;
} else if (std::string(argv[i]) == "--task_sequencing") {
opt_task_sequencing = true;
} else if (std::string(argv[i]) == "--quad_decimate" && i + 1 < argc) {
opt_quad_decimate = std::stoi(argv[i + 1]);
} else if (std::string(argv[i]) == "--no-convergence-threshold") {
convergence_threshold = 0.;
} else if (std::string(argv[i]) == "--help" || std::string(argv[i]) == "-h") {
std::cout
<< argv[0] << " [--ip <default " << opt_robot_ip << ">] [--tag_size <marker size in meter; default "
<< opt_tagSize << ">] [--eMc <eMc extrinsic file>] "
<< "[--quad_decimate <decimation; default " << opt_quad_decimate
<< ">] [--adaptive_gain] [--plot] [--task_sequencing] [--no-convergence-threshold] [--verbose] [--help] [-h]"
<< "\n";
return EXIT_SUCCESS;
}
}
try {
robot.connect(opt_robot_ip);
rs2::config config;
unsigned int width = 640, height = 480;
config.enable_stream(RS2_STREAM_COLOR, 640, 480, RS2_FORMAT_RGBA8, 30);
config.enable_stream(RS2_STREAM_DEPTH, 640, 480, RS2_FORMAT_Z16, 30);
config.enable_stream(RS2_STREAM_INFRARED, 640, 480, RS2_FORMAT_Y8, 30);
rs.open(config);
// Get camera extrinsics
// Set camera extrinsics default values
ePc[0] = 0.0337731;
ePc[1] = -0.00535012;
ePc[2] = -0.0523339;
ePc[3] = -0.247294;
ePc[4] = -0.306729;
ePc[5] = 1.53055;
// If provided, read camera extrinsics from --eMc <file>
if (!opt_eMc_filename.empty()) {
ePc.loadYAML(opt_eMc_filename, ePc);
} else {
std::cout << "Warning, opt_eMc_filename is empty! Use hard coded values."
<< "\n";
}
std::cout << "eMc:\n" << eMc << "\n";
// Get camera intrinsics
std::cout << "cam:\n" << cam << "\n";
vpImage<unsigned char> I(height, width);
#if defined(VISP_HAVE_X11)
vpDisplayX dc(I, 10, 10, "Color image");
#elif defined(VISP_HAVE_GDI)
vpDisplayGDI dc(I, 10, 10, "Color image");
#endif
// vpDetectorAprilTag::vpPoseEstimationMethod poseEstimationMethod = vpDetectorAprilTag::BEST_RESIDUAL_VIRTUAL_VS;
vpDetectorAprilTag detector(tagFamily);
detector.setAprilTagPoseEstimationMethod(poseEstimationMethod);
detector.setDisplayTag(display_tag);
detector.setAprilTagQuadDecimate(opt_quad_decimate);
// Servo
vpHomogeneousMatrix cdMc, cMo, oMo;
// Desired pose used to compute the desired features
vpHomogeneousMatrix cdMo(vpTranslationVector(0, 0, opt_tagSize * 3), // 3 times tag with along camera z axis
vpRotationMatrix({1, 0, 0, 0, -1, 0, 0, 0, -1}));
// Create visual features
std::vector<vpFeaturePoint> p(4), pd(4); // We use 4 points
// Define 4 3D points corresponding to the CAD model of the Apriltag
std::vector<vpPoint> point(4);
point[0].setWorldCoordinates(-opt_tagSize / 2., -opt_tagSize / 2., 0);
point[1].setWorldCoordinates(opt_tagSize / 2., -opt_tagSize / 2., 0);
point[2].setWorldCoordinates(opt_tagSize / 2., opt_tagSize / 2., 0);
point[3].setWorldCoordinates(-opt_tagSize / 2., opt_tagSize / 2., 0);
vpServo task;
// Add the 4 visual feature points
for (size_t i = 0; i < p.size(); i++) {
task.addFeature(p[i], pd[i]);
}
if (opt_adaptive_gain) {
vpAdaptiveGain lambda(1.5, 0.4, 30); // lambda(0)=4, lambda(oo)=0.4 and lambda'(0)=30
task.setLambda(lambda);
} else {
task.setLambda(0.5);
}
vpPlot *plotter = nullptr;
int iter_plot = 0;
if (opt_plot) {
plotter = new vpPlot(2, static_cast<int>(250 * 2), 500, static_cast<int>(I.getWidth()) + 80, 10,
"Real time curves plotter");
plotter->setTitle(0, "Visual features error");
plotter->setTitle(1, "Camera velocities");
plotter->initGraph(0, 8);
plotter->initGraph(1, 6);
plotter->setLegend(0, 0, "error_feat_p1_x");
plotter->setLegend(0, 1, "error_feat_p1_y");
plotter->setLegend(0, 2, "error_feat_p2_x");
plotter->setLegend(0, 3, "error_feat_p2_y");
plotter->setLegend(0, 4, "error_feat_p3_x");
plotter->setLegend(0, 5, "error_feat_p3_y");
plotter->setLegend(0, 6, "error_feat_p4_x");
plotter->setLegend(0, 7, "error_feat_p4_y");
plotter->setLegend(1, 0, "vc_x");
plotter->setLegend(1, 1, "vc_y");
plotter->setLegend(1, 2, "vc_z");
plotter->setLegend(1, 3, "wc_x");
plotter->setLegend(1, 4, "wc_y");
plotter->setLegend(1, 5, "wc_z");
}
bool final_quit = false;
bool has_converged = false;
bool send_velocities = false;
bool servo_started = false;
std::vector<vpImagePoint> *traj_corners = nullptr; // To memorize point trajectory
static double t_init_servo = vpTime::measureTimeMs();
robot.set_eMc(eMc); // Set location of the camera wrt end-effector frame
while (!has_converged && !final_quit) {
double t_start = vpTime::measureTimeMs();
rs.acquire(I);
std::vector<vpHomogeneousMatrix> cMo_vec;
detector.detect(I, opt_tagSize, cam, cMo_vec);
{
std::stringstream ss;
ss << "Left click to " << (send_velocities ? "stop the robot" : "servo the robot") << ", right click to quit.";
vpDisplay::displayText(I, 20, 20, ss.str(), vpColor::red);
}
vpColVector v_c(6);
// Only one tag is detected
if (cMo_vec.size() == 1) {
cMo = cMo_vec[0];
static bool first_time = true;
if (first_time) {
// Introduce security wrt tag positionning in order to avoid PI rotation
std::vector<vpHomogeneousMatrix> v_oMo(2), v_cdMc(2);
v_oMo[1].buildFrom(0, 0, 0, 0, 0, M_PI);
for (size_t i = 0; i < 2; i++) {
v_cdMc[i] = cdMo * v_oMo[i] * cMo.inverse();
}
if (std::fabs(v_cdMc[0].getThetaUVector().getTheta()) < std::fabs(v_cdMc[1].getThetaUVector().getTheta())) {
oMo = v_oMo[0];
} else {
std::cout << "Desired frame modified to avoid PI rotation of the camera" << std::endl;
oMo = v_oMo[1]; // Introduce PI rotation
}
// Compute the desired position of the features from the desired pose
for (size_t i = 0; i < point.size(); i++) {
vpColVector cP, p_;
point[i].changeFrame(cdMo * oMo, cP);
point[i].projection(cP, p_);
pd[i].set_x(p_[0]);
pd[i].set_y(p_[1]);
pd[i].set_Z(cP[2]);
}
}
// Get tag corners
std::vector<vpImagePoint> corners = detector.getPolygon(0);
// Update visual features
for (size_t i = 0; i < corners.size(); i++) {
// Update the point feature from the tag corners location
vpFeatureBuilder::create(p[i], cam, corners[i]);
// Set the feature Z coordinate from the pose
point[i].changeFrame(cMo, cP);
p[i].set_Z(cP[2]);
}
if (opt_task_sequencing) {
if (!servo_started) {
if (send_velocities) {
servo_started = true;
}
t_init_servo = vpTime::measureTimeMs();
}
v_c = task.computeControlLaw((vpTime::measureTimeMs() - t_init_servo) / 1000.);
} else {
v_c = task.computeControlLaw();
}
// Display the current and desired feature points in the image display
vpServoDisplay::display(task, cam, I);
for (size_t i = 0; i < corners.size(); i++) {
std::stringstream ss;
ss << i;
// Display current point indexes
vpDisplay::displayText(I, corners[i] + vpImagePoint(15, 15), ss.str(), vpColor::red);
// Display desired point indexes
vpMeterPixelConversion::convertPoint(cam, pd[i].get_x(), pd[i].get_y(), ip);
vpDisplay::displayText(I, ip + vpImagePoint(15, 15), ss.str(), vpColor::red);
}
if (first_time) {
traj_corners = new std::vector<vpImagePoint>[corners.size()];
}
// Display the trajectory of the points used as features
display_point_trajectory(I, corners, traj_corners);
if (opt_plot) {
plotter->plot(0, iter_plot, task.getError());
plotter->plot(1, iter_plot, v_c);
iter_plot++;
}
if (opt_verbose) {
std::cout << "v_c: " << v_c.t() << std::endl;
}
double error = task.getError().sumSquare();
std::stringstream ss;
ss << "error: " << error;
vpDisplay::displayText(I, 20, static_cast<int>(I.getWidth()) - 150, ss.str(), vpColor::red);
if (opt_verbose)
std::cout << "error: " << error << std::endl;
if (error < convergence_threshold) {
has_converged = true;
std::cout << "Servo task has converged"
<< "\n";
vpDisplay::displayText(I, 100, 20, "Servo task has converged", vpColor::red);
}
if (first_time) {
first_time = false;
}
} // end if (cMo_vec.size() == 1)
else {
v_c = 0;
}
if (!send_velocities) {
v_c = 0;
}
// Send to the robot
{
std::stringstream ss;
ss << "Loop time: " << vpTime::measureTimeMs() - t_start << " ms";
vpDisplay::displayText(I, 40, 20, ss.str(), vpColor::red);
}
if (vpDisplay::getClick(I, button, false)) {
switch (button) {
send_velocities = !send_velocities;
break;
final_quit = true;
v_c = 0;
break;
default:
break;
}
}
}
std::cout << "Stop the robot " << std::endl;
if (opt_plot && plotter != nullptr) {
delete plotter;
plotter = nullptr;
}
if (!final_quit) {
while (!final_quit) {
rs.acquire(I);
vpDisplay::displayText(I, 20, 20, "Click to quit the program.", vpColor::red);
vpDisplay::displayText(I, 40, 20, "Visual servo converged.", vpColor::red);
if (vpDisplay::getClick(I, false)) {
final_quit = true;
}
}
}
if (traj_corners) {
delete[] traj_corners;
}
} catch (const vpException &e) {
std::cout << "ViSP exception: " << e.what() << std::endl;
std::cout << "Stop the robot " << std::endl;
return EXIT_FAILURE;
} catch (const franka::NetworkException &e) {
std::cout << "Franka network exception: " << e.what() << std::endl;
std::cout << "Check if you are connected to the Franka robot"
<< " or if you specified the right IP using --ip command line option set by default to 192.168.1.1. "
<< std::endl;
return EXIT_FAILURE;
} catch (const std::exception &e) {
std::cout << "Franka exception: " << e.what() << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
#else
int main()
{
#if !defined(VISP_HAVE_REALSENSE2)
std::cout << "Install librealsense-2.x" << std::endl;
#endif
#if (VISP_CXX_STANDARD < VISP_CXX_STANDARD_11)
std::cout << "Build ViSP with c++11 or higher compiler flag (cmake -DUSE_CXX_STANDARD=11)." << std::endl;
#endif
#if !defined(VISP_HAVE_FRANKA)
std::cout << "Install libfranka." << std::endl;
#endif
return EXIT_SUCCESS;
}
#endif
Adaptive gain computation.
static bool loadYAML(const std::string &filename, vpArray2D< Type > &A, char *header=NULL)
Definition: vpArray2D.h:652
Generic class defining intrinsic camera parameters.
Implementation of column vector and the associated operations.
Definition: vpColVector.h:131
double sumSquare() const
static const vpColor red
Definition: vpColor.h:217
static const vpColor green
Definition: vpColor.h:220
@ TAG_36h11
AprilTag 36h11 pattern (recommended)
Display for windows using GDI (available on any windows 32 platform).
Definition: vpDisplayGDI.h:129
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 bool getClick(const vpImage< unsigned char > &I, bool blocking=true)
static void display(const vpImage< unsigned char > &I)
static void displayLine(const vpImage< unsigned char > &I, const vpImagePoint &ip1, const vpImagePoint &ip2, const vpColor &color, unsigned int thickness=1, bool segment=true)
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 emited by ViSP classes.
Definition: vpException.h:72
const char * what() const
Definition: vpException.cpp:99
static void create(vpFeaturePoint &s, const vpCameraParameters &cam, const vpDot &d)
Implementation of an homogeneous matrix and operations on such kind of matrices.
vpHomogeneousMatrix inverse() const
Class that defines a 2D point in an image. This class is useful for image processing and stores only ...
Definition: vpImagePoint.h:89
static double distance(const vpImagePoint &iP1, const vpImagePoint &iP2)
unsigned int getWidth() const
Definition: vpImage.h:246
static void convertPoint(const vpCameraParameters &cam, const double &x, const double &y, double &u, double &v)
This class enables real time drawing of 2D or 3D graphics. An instance of the class open a window whi...
Definition: vpPlot.h:116
void initGraph(unsigned int graphNum, unsigned int curveNbr)
Definition: vpPlot.cpp:205
void setLegend(unsigned int graphNum, unsigned int curveNum, const std::string &legend)
Definition: vpPlot.cpp:534
void plot(unsigned int graphNum, unsigned int curveNum, double x, double y)
Definition: vpPlot.cpp:285
void setTitle(unsigned int graphNum, const std::string &title)
Definition: vpPlot.cpp:497
Implementation of a pose vector and operations on poses.
Definition: vpPoseVector.h:152
void acquire(vpImage< unsigned char > &grey, double *ts=NULL)
vpCameraParameters getCameraParameters(const rs2_stream &stream, vpCameraParameters::vpCameraParametersProjType type=vpCameraParameters::perspectiveProjWithDistortion, int index=-1) const
bool open(const rs2::config &cfg=rs2::config())
void setVelocity(const vpRobot::vpControlFrameType frame, const vpColVector &vel)
@ CAMERA_FRAME
Definition: vpRobot.h:83
@ STATE_VELOCITY_CONTROL
Initialize the velocity controller.
Definition: vpRobot.h:67
@ STATE_STOP
Stops robot motion especially in velocity and acceleration control.
Definition: vpRobot.h:66
virtual vpRobotStateType setRobotState(const vpRobot::vpRobotStateType newState)
Definition: vpRobot.cpp:201
Implementation of a rotation matrix and operations on such kind of matrices.
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 setLambda(double c)
Definition: vpServo.h:404
void setServo(const vpServoType &servo_type)
Definition: vpServo.cpp:215
vpColVector getError() const
Definition: vpServo.h:278
vpColVector computeControlLaw()
Definition: vpServo.cpp:926
@ CURRENT
Definition: vpServo.h:182
void addFeature(vpBasicFeature &s, vpBasicFeature &s_star, unsigned int select=vpBasicFeature::FEATURE_ALL)
Definition: vpServo.cpp:487
Class that consider the case of a translation vector.
VISP_EXPORT double measureTimeMs()