chainiksolverpos_lma_demo.cpp

Go to the documentation of this file.

/**************************************************************************
    begin                : May 2011
    copyright            : (C) 2011 Erwin Aertbelien
    email                : firstname.lastname@mech.kuleuven.ac.be

 History (only major changes)( AUTHOR-Description ) :

 ***************************************************************************
 *   This library is free software; you can redistribute it and/or         *
 *   modify it under the terms of the GNU Lesser General Public            *
 *   License as published by the Free Software Foundation; either          *
 *   version 2.1 of the License, or (at your option) any later version.    *
 *                                                                         *
 *   This library is distributed in the hope that it will be useful,       *
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of        *
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU     *
 *   Lesser General Public License for more details.                       *
 *                                                                         *
 *   You should have received a copy of the GNU Lesser General Public      *
 *   License along with this library; if not, write to the Free Software   *
 *   Foundation, Inc., 59 Temple Place,                                    *
 *   Suite 330, Boston, MA  02111-1307  USA                                *
 *                                                                         *
 ***************************************************************************/

#include <iostream>
#include <frames_io.hpp>
#include <models.hpp>
#include <chainiksolverpos_lma.hpp>
#include <chainfksolverpos_recursive.hpp>
#include <boost/timer.hpp>

void test_inverseposkin(KDL::Chain& chain) {
        using namespace KDL;
        using namespace std;
        boost::timer timer;
        int num_of_trials = 1000000;
        int total_number_of_iter = 0;
        int n = chain.getNrOfJoints();
        int nrofresult_ok = 0;
        int nrofresult_minus1=0;
        int nrofresult_minus2=0;
        int nrofresult_minus3=0;
        int min_num_of_iter = 10000000;
        int max_num_of_iter = 0;
        double min_diff = 1E10;
        double max_diff = 0;
        double min_trans_diff = 1E10;
        double max_trans_diff = 0;
        double min_rot_diff = 1E10;
        double max_rot_diff = 0;
        Eigen::Matrix<double,6,1> L;
        L(0)=1;L(1)=1;L(2)=1;
        L(3)=0.01;L(4)=0.01;L(5)=0.01;
        ChainFkSolverPos_recursive fwdkin(chain);
        ChainIkSolverPos_LMA solver(chain,L);
        JntArray q(n);
        JntArray q_init(n);
        JntArray q_sol(n);
        for (int trial=0;trial<num_of_trials;++trial) {
                q.data.setRandom();
                q.data *= M_PI;
                q_init.data.setRandom();
                q_init.data *= M_PI;
                Frame pos_goal,pos_reached;
                fwdkin.JntToCart(q,pos_goal);
                //solver.compute_fwdpos(q.data);
                //pos_goal = solver.T_base_head;
                int retval;
                retval = solver.CartToJnt(q_init,pos_goal,q_sol);
                switch (retval) {
                case 0:
                        nrofresult_ok++;
                        break;
                case -1:
                        nrofresult_minus1++;
                        break;
                case -2:
                        nrofresult_minus2++;
                        break;
                case -3:
                        nrofresult_minus3++;
                        break;
                }
                if (retval !=0) {
                        cout << "-------------- failed ----------------------------" << endl;
                        cout << "pos " << pos_goal << endl;
                        cout << "reached pos " << solver.T_base_head << endl;
                        cout << "TF from pos to head \n" << pos_goal.Inverse()*solver.T_base_head << endl;
                        cout << "gradient " << solver.grad.transpose() << endl;
                        cout << "q   " << q.data.transpose()/M_PI*180.0 << endl;
                        cout << "q_sol " << q_sol.data.transpose()/M_PI*180.0 << endl;
                        cout << "q_init " << q_init.data.transpose()/M_PI*180.0 << endl;
                        cout << "return value " << retval << endl;
                        cout << "last #iter " << solver.lastNrOfIter << endl;
                        cout << "last diff  " << solver.lastDifference << endl;
                        cout << "jacobian of goal values ";
                        solver.display_jac(q);
                        std::cout << "jacobian of solved values ";
                        solver.display_jac(q_sol);

                }
                total_number_of_iter += solver.lastNrOfIter;
                if (solver.lastNrOfIter > max_num_of_iter) max_num_of_iter = solver.lastNrOfIter;
                if (solver.lastNrOfIter < min_num_of_iter) min_num_of_iter = solver.lastNrOfIter;
                if (retval!=-3) {
                if (solver.lastDifference > max_diff) max_diff = solver.lastDifference;
                if (solver.lastDifference < min_diff) min_diff = solver.lastDifference;

                if (solver.lastTransDiff > max_trans_diff) max_trans_diff = solver.lastTransDiff;
                if (solver.lastTransDiff < min_trans_diff) min_trans_diff = solver.lastTransDiff;

                if (solver.lastRotDiff > max_trans_diff) max_rot_diff = solver.lastRotDiff;
                if (solver.lastRotDiff < min_trans_diff) min_rot_diff = solver.lastRotDiff;
                }
                fwdkin.JntToCart(q_sol,pos_reached);
        }
        cout << "------------------ statistics ------------------------------"<<endl;
        cout << "#times successful " << nrofresult_ok << endl;
        cout << "#times -1 result " << nrofresult_minus1 << endl;
        cout << "#times -2 result " << nrofresult_minus2 << endl;
        cout << "#times -3 result " << nrofresult_minus3 << endl;
        cout << "average number of iter " << (double)total_number_of_iter/(double)num_of_trials << endl;
        cout << "min. nr of iter " << min_num_of_iter << endl;
        cout << "max. nr of iter " << max_num_of_iter << endl;
        cout << "min. difference after solving " << min_diff << endl;
        cout << "max. difference after solving " << max_diff << endl;
        cout << "min. trans. difference after solving " << min_trans_diff << endl;
        cout << "max. trans. difference after solving " << max_trans_diff << endl;
        cout << "min. rot. difference after solving " << min_rot_diff << endl;
        cout << "max. rot. difference after solving " << max_rot_diff << endl;
        double el = timer.elapsed();
        cout << "elapsed time " << el << endl;
        cout << "estimate of average time per invposkin (ms)" << el/num_of_trials*1000 << endl;
        cout << "estimate of longest time per invposkin (ms) " << el/total_number_of_iter*max_num_of_iter *1000 << endl;
        cout << "estimate of shortest time per invposkin (ms) " << el/total_number_of_iter*min_num_of_iter *1000 << endl;
}

int main(int argc,char* argv[]) {
        std::cout <<
                        " This example generates random joint positions, applies a forward kinematic transformation,\n"
                <<  " and calls ChainIkSolverPos_LMA on the resulting pose.  In this way we are sure that\n"
                <<  " the resulting pose is reachable.  However, some percentage of the trials will be at\n"
                <<  " near singular position, where it is more difficult to achieve convergence and accuracy\n"
                <<  " The initial position given to the algorithm is also a random joint position\n"
                <<  " This routine asks for an accuracy of 10 micrometer, one order of magnitude better than a\n"
                <<  " a typical industrial robot.\n"
                <<  " This routine can take more then 6 minutes to execute. It then gives statistics on execution times\n"
                <<  " and failures.\n"
                <<  " Typically when executed 1 000 000 times, you will still see some small amount of failures\n"
                <<  " Typically these failures are in the neighbourhoud of singularities.  Most failures of type -2 still\n"
                <<  " reach an accuracy better than 1E-4.\n"
                <<  " This is much better than ChainIkSolverPos_NR, which fails a few times per 100 trials.\n";
        using namespace KDL;
        Chain chain;
        chain = KDL::Puma560();
        //chain = KDL::KukaLWR_DHnew();

        ChainIkSolverPos_LMA solver(chain);

        test_inverseposkin(chain);

    return 0;
}