Minimum jerk Cartesian trajectory following
Note
The source code for this example can be found in [orca_root]/examples/gazebo/06-trajectory_following.cc
, or alternatively on github at: https://github.com/syroco/orca/blob/dev/examples/gazebo/06-trajectory_following.cc
Full Code Listing
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// 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>
#include <orca/gazebo/GazeboServer.h>
#include <orca/gazebo/GazeboModel.h>
using namespace orca::all;
using namespace orca::gazebo;
class MinJerkPositionTrajectory {
private:
Eigen::Vector3d alpha_, sp_, ep_;
double duration_ = 0.0;
double start_time_ = 0.0;
bool first_call_ = true;
bool traj_finished_ = false;
public:
MinJerkPositionTrajectory (double duration)
: duration_(duration)
{
}
bool isTrajectoryFinished(){return traj_finished_;}
void resetTrajectory(const Eigen::Vector3d& start_position, const Eigen::Vector3d& end_position)
{
sp_ = start_position;
ep_ = end_position;
alpha_ = ep_ - sp_;
first_call_ = true;
traj_finished_ = false;
}
void getDesired(double current_time, Eigen::Vector3d& p, Eigen::Vector3d& v, Eigen::Vector3d& a)
{
if(first_call_)
{
start_time_ = current_time;
first_call_ = false;
}
double tau = (current_time - start_time_) / duration_;
if(tau >= 1.0)
{
p = ep_;
v = Eigen::Vector3d::Zero();
a = Eigen::Vector3d::Zero();
traj_finished_ = true;
return;
}
p = sp_ + alpha_ * ( 10*pow(tau,3.0) - 15*pow(tau,4.0) + 6*pow(tau,5.0) );
v = Eigen::Vector3d::Zero() + alpha_ * ( 30*pow(tau,2.0) - 60*pow(tau,3.0) + 30*pow(tau,4.0) );
a = Eigen::Vector3d::Zero() + alpha_ * ( 60*pow(tau,1.0) - 180*pow(tau,2.0) + 120*pow(tau,3.0) );
}
};
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));
orca::optim::Controller controller(
"controller"
,robot_model
,orca::optim::ResolutionStrategy::OneLevelWeighted
,QPSolverImplType::qpOASES
);
const int ndof = robot_model->getNrOfDegreesOfFreedom();
auto joint_pos_task = controller.addTask<JointAccelerationTask>("JointPosTask");
// Eigen::VectorXd P(ndof);
// P.setConstant(100);
joint_pos_task->pid()->setProportionalGain(Eigen::VectorXd::Constant(ndof, 100));
// Eigen::VectorXd I(ndof);
// I.setConstant(1);
joint_pos_task->pid()->setDerivativeGain(Eigen::VectorXd::Constant(ndof, 1));
// Eigen::VectorXd windupLimit(ndof);
// windupLimit.setConstant(10);
joint_pos_task->pid()->setWindupLimit(Eigen::VectorXd::Constant(ndof, 10));
// Eigen::VectorXd D(ndof);
// D.setConstant(10);
joint_pos_task->pid()->setDerivativeGain(Eigen::VectorXd::Constant(ndof, 10));
joint_pos_task->setWeight(1.e-6);
auto cart_acc_pid = std::make_shared<CartesianAccelerationPID>("CartTask_EE-servo_controller");
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");
auto cart_task = controller.addTask<CartesianTask>("CartTask_EE");
cart_task->setServoController(cart_acc_pid);
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);
GazeboServer gzserver(argc,argv);
auto gz_model = GazeboModel(gzserver.insertModelFromURDFFile(urdf_url));
gz_model.setModelConfiguration( { "joint_0", "joint_3","joint_5"} , {1.0,-M_PI/2.,M_PI/2.});
///////////////////////////////////////
///////////////////////////////////////
///////////////////////////////////////
///////////////////////////////////////
MinJerkPositionTrajectory traj(5.0);
int traj_loops = 0;
Eigen::Vector3d start_position, end_position;
Eigen::VectorXd controller_torques(ndof);
Eigen::Affine3d desired_cartesian_pose;
Vector6d desired_cartesian_vel = Vector6d::Zero();
Vector6d desired_cartesian_acc = Vector6d::Zero();
cart_task->onActivationCallback([](){
std::cout << "Activating CartesianTask..." << '\n';
});
cart_task->onActivatedCallback([&](){
desired_cartesian_pose = cart_acc_pid->getCurrentCartesianPose();
Eigen::Quaterniond quat = orca::math::quatFromRPY(M_PI,0,0); // make it point to the table
desired_cartesian_pose.linear() = quat.toRotationMatrix();
start_position = desired_cartesian_pose.translation();
end_position = start_position + Eigen::Vector3d(0,-0.35,-.3);
traj.resetTrajectory(start_position, end_position);
});
cart_task->onComputeBeginCallback([&](double current_time, double dt){
if (cart_task->getState() == TaskBase::State::Activated)
{
Eigen::Vector3d p, v, a;
traj.getDesired(current_time, p, v, a);
desired_cartesian_pose.translation() = p;
desired_cartesian_vel.head(3) = v;
desired_cartesian_acc.head(3) = a;
cart_acc_pid->setDesired(desired_cartesian_pose.matrix(),desired_cartesian_vel,desired_cartesian_acc);
}
});
cart_task->onComputeEndCallback([&](double current_time, double dt){
if (cart_task->getState() == TaskBase::State::Activated)
{
if (traj.isTrajectoryFinished() )
{
if (traj_loops < 10)
{
// flip start and end positions.
auto ep = end_position;
end_position = start_position;
start_position = ep;
traj.resetTrajectory(start_position, end_position);
std::cout << "Changing trajectory direction. [" << traj_loops << " of 10]" << '\n';
++traj_loops;
}
else
{
std::cout << "Trajectory looping finished. Deactivating task and starting gravity compensation." << '\n';
cart_task->deactivate();
}
}
}
});
cart_task->onDeactivationCallback([&](){
std::cout << "Deactivating task." << '\n';
std::cout << "\n\n\n" << '\n';
std::cout << "Last controller_torques:\n" << controller_torques << '\n';
});
cart_task->onDeactivatedCallback([&](){
std::cout << "CartesianTask deactivated." << '\n';
});
// Lets decide that the robot is gravity compensated
// So we need to remove G(q) from the solution
controller.removeGravityTorquesFromSolution(true);
gz_model.executeAfterWorldUpdate([&](uint32_t n_iter,double current_time,double dt)
{
robot_model->setRobotState(gz_model.getWorldToBaseTransform().matrix()
,gz_model.getJointPositions()
,gz_model.getBaseVelocity()
,gz_model.getJointVelocities()
,gz_model.getGravity()
);
gz_model.setJointGravityTorques(robot_model->getJointGravityTorques());
// All tasks need the robot to be initialized during the activation phase
if(n_iter == 1)
controller.activateTasksAndConstraints();
controller.update(current_time, dt);
if(controller.solutionFound())
{
controller_torques = controller.getJointTorqueCommand();
gz_model.setJointTorqueCommand( controller_torques );
}
else
{
gz_model.setBrakes(true);
}
});
std::cout << "Simulation running... (GUI with \'gzclient\')" << '\n';
// If you want to pause the simulation before starting it uncomment these lines
// Note that to unlock it either open 'gzclient' and click on the play button
// Or open a terminal and type 'gz world -p false'
//
std::cout << "Gazebo is paused, open gzclient to unpause it or type 'gz world -p false' in a new terminal" << '\n';
gazebo::event::Events::pause.Signal(true);
gzserver.run();
return 0;
}
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