unified_joint_limit_singularity_solver.cpp

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/*
 * Copyright 2017 Fraunhofer Institute for Manufacturing Engineering and Automation (IPA)
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
 
 
#include "cob_twist_controller/constraint_solvers/solvers/unified_joint_limit_singularity_solver.h"
 
Eigen::MatrixXd UnifiedJointLimitSingularitySolver::solve(const Vector6d_t& in_cart_velocities,
                                               const JointStates& joint_states)
{
 
    Eigen::JacobiSVD<Eigen::MatrixXd> svd(this->jacobian_data_, Eigen::ComputeThinU | Eigen::ComputeThinV);
    Eigen::MatrixXd J=this->jacobian_data_;
    Eigen::MatrixXd J_T=J.transpose();
    Eigen::MatrixXd U=svd.matrixU();
    Eigen::MatrixXd U_T =U.transpose();
 
    Eigen::MatrixXd Q = this->calculateWeighting(in_cart_velocities, joint_states);
 
    Eigen::MatrixXd Wt=Q*svd.matrixV();
    Eigen::MatrixXd Wt_T=Wt.transpose();
/*
    Eigen::VectorXd singularValues = svd.singularValues();
    for (int i=0;i<singularValues.rows();i++){
        singularValues(i)=singularValues(i)*Q(i,i);
    }
    Eigen::MatrixXd lambda = damping_->getDampingFactor(singularValues, this->jacobian_data_);
 
    Eigen::MatrixXd Ulambda =U*lambda;
    Eigen::MatrixXd UlambdaUt =Ulambda*U_T;
 
    Eigen::MatrixXd WtWt_T= Wt*Wt_T;
    Eigen::MatrixXd JWtWt_T=J*Wt*Wt_T;
    Eigen::MatrixXd JWtWt_TJ_T=JWtWt_T*J_T;
 
    Eigen::MatrixXd J_robust=JWtWt_TJ_T+UlambdaUt;
 
 
    Eigen::MatrixXd pinv=J_robust.inverse();
    Eigen::MatrixXd J_Tpinv= J_T*pinv;
    Eigen::MatrixXd WtWt_TJ_Tpinv= WtWt_T*J_Tpinv;
    Eigen::MatrixXd qdots_out =WtWt_TJ_Tpinv*in_cart_velocities;*/
 
    Eigen::MatrixXd J_robust=J*Wt*Wt_T*J_T;
    Eigen::MatrixXd pinv=pinv_calc_.calculate(this->params_, this->damping_, J_robust);
    Eigen::MatrixXd qdots_out =Wt*Wt_T*J_T*pinv*in_cart_velocities;
 
    return qdots_out;
}
 
Eigen::MatrixXd UnifiedJointLimitSingularitySolver::calculateWeighting(const Vector6d_t& in_cart_velocities, const JointStates& joint_states) const
{
    Eigen::MatrixXd Jinv = pinv_calc_.calculate(this->params_, this->damping_, this->jacobian_data_);
    Eigen::VectorXd q_dot = Jinv * in_cart_velocities;
    std::vector<double> limits_min = this->limiter_params_.limits_min;
    std::vector<double> limits_max = this->limiter_params_.limits_max;
    uint32_t cols = this->jacobian_data_.cols();
 
    Eigen::VectorXd weighting = Eigen::VectorXd::Zero(cols);
    Eigen::VectorXd weighting_pos = Eigen::VectorXd::Zero(cols);
    Eigen::VectorXd weighting_speed = Eigen::VectorXd::Zero(cols);
 
    KDL::JntArray q = joint_states.current_q_;
 
    double sigma = this->params_.ujs_solver_params.sigma;
    double sigma_speed = this->params_.ujs_solver_params.sigma_speed;
    double delta_pos = this->params_.ujs_solver_params.delta_pos;
    double delta_speed = this->params_.ujs_solver_params.delta_speed;
    for (uint32_t i = 0; i < cols ; ++i)
    {
 
        weighting(i) = (1.0/(1.0+exp(-(q(i)-limits_min[i]-delta_pos)/sigma)))*(1.0/(1.0+exp((q(i)-limits_max[i]+delta_pos)/sigma)))+(1.0/(1.0+exp((q(i)*q_dot(i)+delta_speed)*sigma_speed)));
 
        if( (fabs(q(i)-limits_min[i])<params_.limiter_params.limits_tolerance*M_PI/180.0)){
            ROS_WARN("Joint %i tolerance distance to minimum position %f not respected",i,(fabs(q(i)-limits_min[i])));
        }
        if( (fabs(q(i)-limits_max[i])<params_.limiter_params.limits_tolerance*M_PI/180.0) ){
            ROS_WARN("Joint %i tolerance distance to maximum position %f not respected",i,(fabs(q(i)-limits_max[i])));
        }
        if( (fabs(q(i)-limits_min[i])<0.0)){
            ROS_ERROR("Joint %i distance to minimum position %f not respected",i,(fabs(q(i)-limits_min[i])));
        }
        if( (fabs(q(i)-limits_max[i])<0.0)){
            ROS_ERROR("Joint %i distance to maximum position %f not respected",i,(fabs(q(i)-limits_max[i])));
        }
 
        if(weighting(i)>1.0){
            weighting(i)=1.0;
        }
    }
 
    return weighting.asDiagonal();
}