API  4.3
For MATLAB, Python, Java, and C++ users
exampleMocoCustomEffortGoal.cpp

This example shows creating a custom goal in a plugin library, which allows you to use the custom goal in C++, the command-line, Matlab, Python, and the GUI.See Defining a custom goal or cost.

/* -------------------------------------------------------------------------- *
* OpenSim Moco: exampleMocoCustomEffortGoal.cpp *
* -------------------------------------------------------------------------- *
* Copyright (c) 2019 Stanford University and the Authors *
* *
* Author(s): Christopher Dembia *
* *
* 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 "MocoCustomEffortGoal.h"
#include <OpenSim/Actuators/ActivationCoordinateActuator.h>
#include <OpenSim/Moco/osimMoco.h>
using namespace OpenSim;
std::unique_ptr<Model> createSlidingMassModel() {
auto model = make_unique<Model>();
model->setName("sliding_mass");
model->set_gravity(SimTK::Vec3(0, 0, 0));
auto* body = new Body("body", 2.0, SimTK::Vec3(0), SimTK::Inertia(0));
model->addComponent(body);
// Allows translation along x.
auto* joint = new SliderJoint("slider", model->getGround(), *body);
coord.setName("position");
model->addComponent(joint);
auto* actu = new CoordinateActuator();
actu->setCoordinate(&coord);
actu->setName("actuator");
actu->setOptimalForce(1);
model->addComponent(actu);
body->attachGeometry(new Sphere(0.05));
model->finalizeConnections();
return model;
}
int main() {
MocoStudy study;
study.setName("sliding_mass");
// Define the optimal control problem.
// ===================================
MocoProblem& problem = study.updProblem();
// Model (dynamics).
// -----------------
problem.setModel(createSlidingMassModel());
// Bounds.
// -------
// Initial time must be 0, final time can be within [0, 5].
// Initial position must be 0, final position must be 1.
problem.setStateInfo("/slider/position/value", MocoBounds(-5, 5),
// Initial and final speed must be 0. Use compact syntax.
problem.setStateInfo("/slider/position/speed", {-50, 50}, 0, 0);
// Applied force must be between -50 and 50.
problem.setControlInfo("/actuator", MocoBounds(-50, 50));
// Cost.
// -----
problem.addGoal<MocoFinalTimeGoal>("time");
// Use the goal from the plugin:
problem.addGoal<MocoCustomEffortGoal>("effort");
// Configure the solver.
// =====================
solver.set_verbosity(2);
solver.set_optim_solver("ipopt");
solver.set_optim_ipopt_print_level(4);
solver.set_optim_max_iterations(50);
solver.set_optim_finite_difference_scheme("forward");
solver.set_optim_sparsity_detection("random");
solver.set_optim_write_sparsity("sliding_mass");
// Specify an initial guess.
// -------------------------
MocoTrajectory guess = solver.createGuess("bounds");
guess.setTime({0, 0.5});
guess.setState("/slider/position/value", {0.0, 1.0});
solver.setGuess(guess);
// Solve the problem.
// ==================
MocoSolution solution = study.solve();
std::cout << "Solution status: " << solution.getStatus() << std::endl;
study.visualize(solution);
return EXIT_SUCCESS;
}