Simulating the controller performance
Note
The source code for this example can be found in [orca_root]/examples/basic/02-simulating_results.cc
, or alternatively on github at: https://github.com/syroco/orca/blob/dev/examples/basic/02-simulating_results.cc
Full Code Listing
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 | // This file is a part of the ORCA framework.
// Copyright 2017, ISIR / Universite Pierre et Marie Curie (UPMC)
// Copyright 2018, Fuzzy Logic Robotics
// Main contributor(s): Antoine Hoarau, Ryan Lober, and
// Fuzzy Logic Robotics <info@fuzzylogicrobotics.com>
//
// ORCA is a whole-body reactive controller framework for robotics.
//
// This software is governed by the CeCILL-C license under French law and
// abiding by the rules of distribution of free software. You can use,
// modify and/ or redistribute the software under the terms of the CeCILL-C
// license as circulated by CEA, CNRS and INRIA at the following URL
// "http://www.cecill.info".
//
// As a counterpart to the access to the source code and rights to copy,
// modify and redistribute granted by the license, users are provided only
// with a limited warranty and the software's author, the holder of the
// economic rights, and the successive licensors have only limited
// liability.
//
// In this respect, the user's attention is drawn to the risks associated
// with loading, using, modifying and/or developing or reproducing the
// software by the user in light of its specific status of free software,
// that may mean that it is complicated to manipulate, and that also
// therefore means that it is reserved for developers and experienced
// professionals having in-depth computer knowledge. Users are therefore
// encouraged to load and test the software's suitability as regards their
// requirements in conditions enabling the security of their systems and/or
// data to be ensured and, more generally, to use and operate it in the
// same conditions as regards security.
//
// The fact that you are presently reading this means that you have had
// knowledge of the CeCILL-C license and that you accept its terms.
/** @file
@copyright 2018 Fuzzy Logic Robotics <info@fuzzylogicrobotics.com>
@author Antoine Hoarau
@author Ryan Lober
*/
#include <orca/orca.h>
using namespace orca::all;
int main(int argc, char const *argv[])
{
if(argc < 2)
{
std::cerr << "Usage : " << argv[0] << " /path/to/robot-urdf.urdf (optionally -l debug/info/warning/error)" << "\n";
return -1;
}
std::string urdf_url(argv[1]);
orca::utils::Logger::parseArgv(argc, argv);
auto robot_model = std::make_shared<RobotModel>();
robot_model->loadModelFromFile(urdf_url);
robot_model->setBaseFrame("base_link");
robot_model->setGravity(Eigen::Vector3d(0,0,-9.81));
RobotState eigState;
eigState.resize(robot_model->getNrOfDegreesOfFreedom());
eigState.jointPos.setZero();
eigState.jointVel.setZero();
robot_model->setRobotState(eigState.jointPos,eigState.jointVel);
orca::optim::Controller controller(
"controller"
,robot_model
,orca::optim::ResolutionStrategy::OneLevelWeighted
,QPSolverImplType::qpOASES
);
// Create the servo controller that the cartesian task needs
auto cart_acc_pid = std::make_shared<CartesianAccelerationPID>("servo_controller");
// Now set the servoing PID
Vector6d P;
P << 1000, 1000, 1000, 10, 10, 10;
cart_acc_pid->pid()->setProportionalGain(P);
Vector6d D;
D << 100, 100, 100, 1, 1, 1;
cart_acc_pid->pid()->setDerivativeGain(D);
cart_acc_pid->setControlFrame("link_7");
Eigen::Affine3d cart_pos_ref;
cart_pos_ref.translation() = Eigen::Vector3d(1.,0.75,0.5); // x,y,z in meters
cart_pos_ref.linear() = Eigen::Quaterniond::Identity().toRotationMatrix();
// Set the desired cartesian velocity and acceleration to zero
Vector6d cart_vel_ref = Vector6d::Zero();
Vector6d cart_acc_ref = Vector6d::Zero();
// The desired values are set on the servo controller. Because cart_task->setDesired expects a cartesian acceleration. Which is computed automatically by the servo controller
cart_acc_pid->setDesired(cart_pos_ref.matrix(),cart_vel_ref,cart_acc_ref);
// Set the servo controller to the cartesian task
auto cart_task = controller.addTask<CartesianTask>("CartTask_EE");
cart_task->setServoController(cart_acc_pid);
// ndof
const int ndof = robot_model->getNrOfDegreesOfFreedom();
auto jnt_trq_cstr = controller.addConstraint<JointTorqueLimitConstraint>("JointTorqueLimit");
Eigen::VectorXd jntTrqMax(ndof);
jntTrqMax.setConstant(200.0);
jnt_trq_cstr->setLimits(-jntTrqMax,jntTrqMax);
auto jnt_pos_cstr = controller.addConstraint<JointPositionLimitConstraint>("JointPositionLimit");
auto jnt_vel_cstr = controller.addConstraint<JointVelocityLimitConstraint>("JointVelocityLimit");
Eigen::VectorXd jntVelMax(ndof);
jntVelMax.setConstant(2.0);
jnt_vel_cstr->setLimits(-jntVelMax,jntVelMax);
controller.activateTasksAndConstraints();
// for each task, it calls task->activate(), that can call onActivationCallback() if it is set.
// To set it :
// task->setOnActivationCallback([&]()
// {
// // Do some initialisation here
// });
// Note : you need to set it BEFORE calling
// controller.activateTasksAndConstraints();
double dt = 0.001;
double current_time = 0.0;
Eigen::VectorXd trq_cmd(ndof);
Eigen::VectorXd acc_new(ndof);
controller.update(current_time, dt);
current_time += dt;
controller.print();
std::cout << "\n\n\n" << '\n';
std::cout << "====================================" << '\n';
//std::cout << "Initial State:\n" << cart_task->servoController()->getCurrentCartesianPose() << '\n';
std::cout << "Desired State:\n" << cart_pos_ref.matrix() << '\n';
std::cout << "====================================" << '\n';
std::cout << "\n\n\n" << '\n';
std::cout << "Begining Simulation..." << '\n';
int print_counter = 0;
for (; current_time < 10.0; current_time +=dt)
{
if(print_counter == 100)
{
std::cout << "Task position at t = " << current_time << "\t---\t" << cart_acc_pid->getCurrentCartesianPose().block(0,3,3,1).transpose() << '\n';
print_counter = 0;
}
++print_counter;
controller.update(current_time, dt);
if(controller.solutionFound())
{
trq_cmd = controller.getJointTorqueCommand();
}
else
{
std::cout << "[warning] Didn't find a solution. Stopping simulation." << '\n';
break;
}
acc_new = robot_model->getMassMatrix().ldlt().solve(trq_cmd - robot_model->getJointGravityAndCoriolisTorques());
eigState.jointPos += eigState.jointVel * dt + ((acc_new*dt*dt)/2);
eigState.jointVel += acc_new * dt;
robot_model->setRobotState(eigState.jointPos,eigState.jointVel);
}
std::cout << "Simulation finished." << '\n';
std::cout << "\n\n\n" << '\n';
std::cout << "====================================" << '\n';
//std::cout << "Final State:\n" << cart_task->servoController()->getCurrentCartesianPose() << '\n';
//std::cout << "Position error:\n" << cart_task->servoController()->getCurrentCartesianPose().block(0,3,3,1) - cart_pos_ref.translation() << '\n';
// All objets will be destroyed here
return 0;
}
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