exampleMocoTrack.cpp

This is an example using the MocoTrack tool with a complex model to track walking.

/* -------------------------------------------------------------------------- *
 * OpenSim Moco: exampleMocoTrack.cpp                                         *
 * -------------------------------------------------------------------------- *
 * Copyright (c) 2023 Stanford University and the Authors                     *
 *                                                                            *
 * Author(s): Nicholas Bianco                                                 *
 *                                                                            *
 * 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 <OpenSim/Actuators/CoordinateActuator.h>
#include <OpenSim/Actuators/ModelOperators.h>
#include <OpenSim/Moco/osimMoco.h>

using namespace OpenSim;

void torqueDrivenMarkerTracking() {

    // Create and name an instance of the MocoTrack tool.
    MocoTrack track;
    track.setName("torque_driven_marker_tracking");

    // Construct a ModelProcessor and add it to the tool. ModelProcessors
    // accept a base model (or model file) and allow you to easily modify the
    // model by appending ModelOperators. Operations are performed in the order
    // that they are appended to the model.
    ModelProcessor modelProcessor("subject_walk_scaled.osim");
    // Add ground reaction external loads in lieu of a ground-contact model.
    modelProcessor.append(ModOpAddExternalLoads("grf_walk.xml") );
    // Remove all the muscles in the model's ForceSet.
    modelProcessor.append(ModOpRemoveMuscles());
    // Add CoordinateActuators to the model degrees-of-freedom. This
    // ignores the pelvis coordinates which already have residual
    // CoordinateActuators.
    modelProcessor.append(ModOpAddReserves(250.0, 1.0));
    track.setModel(modelProcessor);
    // In C++, you could alternatively use the pipe operator '|' to
    // append ModelOperators:
    //   track.setModel(ModelProcessor("model.osim") | ModOpAddReserves(250));

    // Use this convenience function to set the MocoTrack markers reference
    // directly from a TRC file. By default, the marker data is filtered at
    //  6 Hz
    track.setMarkersReferenceFromTRC("marker_trajectories.trc");

    // There is marker data in the 'marker_trajectories.trc' associated with
    // model markers that no longer exists (i.e. markers on the arms). Set this
    // flag to avoid an exception from being thrown.
    track.set_allow_unused_references(true);

    // Increase the global marker tracking weight, which is the weight
    // associated with the internal MocoMarkerTrackingGoal term.
    track.set_markers_global_tracking_weight(10);

    // Increase the tracking weights for individual markers in the data set 
    // placed on bony landmarks compared to markers located on soft tissue.
    MocoWeightSet markerWeights;
    markerWeights.cloneAndAppend({"R.ASIS", 20});
    markerWeights.cloneAndAppend({"L.ASIS", 20});
    markerWeights.cloneAndAppend({"R.PSIS", 20});
    markerWeights.cloneAndAppend({"L.PSIS", 20});
    markerWeights.cloneAndAppend({"R.Knee", 10});
    markerWeights.cloneAndAppend({"R.Ankle", 10});
    markerWeights.cloneAndAppend({"R.Heel", 10});
    markerWeights.cloneAndAppend({"R.MT5", 5});
    markerWeights.cloneAndAppend({"R.Toe", 2});
    markerWeights.cloneAndAppend({"L.Knee", 10});
    markerWeights.cloneAndAppend({"L.Ankle", 10});
    markerWeights.cloneAndAppend({"L.Heel", 10});
    markerWeights.cloneAndAppend({"L.MT5", 5});
    markerWeights.cloneAndAppend({"L.Toe", 2});
    track.set_markers_weight_set(markerWeights);

    // Initial time, final time, and mesh interval. The number of mesh points
    // used to discretize the problem is computed internally using these values.
    track.set_initial_time(0.48);
    track.set_final_time(1.61);
    track.set_mesh_interval(0.02);

    // Solve! Use track.solve() to skip visualizing.
    MocoSolution solution = track.solveAndVisualize();
}

void muscleDrivenStateTracking() {

    // Create and name an instance of the MocoTrack tool.
    MocoTrack track;
    track.setName("muscle_driven_state_tracking");

    // Construct a ModelProcessor and set it on the tool. The default
    // muscles in the model are replaced with optimization-friendly
    // DeGrooteFregly2016Muscles, and adjustments are made to the default muscle
    // parameters.
    ModelProcessor modelProcessor("subject_walk_scaled.osim");
    modelProcessor.append(ModOpAddExternalLoads("grf_walk.xml"));
    modelProcessor.append(ModOpIgnoreTendonCompliance());
    modelProcessor.append(ModOpReplaceMusclesWithDeGrooteFregly2016());
    // Only valid for DeGrooteFregly2016Muscles.
    modelProcessor.append(ModOpIgnorePassiveFiberForcesDGF());
    // Only valid for DeGrooteFregly2016Muscles.
    modelProcessor.append(ModOpScaleActiveFiberForceCurveWidthDGF(1.5));
    // Use a function-based representation for the muscle paths. This is
    // recommended to speed up convergence, but if you would like to use
    // the original GeometryPath muscle wrapping instead, simply comment out
    // this line. To learn how to create a set of function-based paths for
    // your model, see the example 'examplePolynomialPathFitter.py/.m'.
    modelProcessor.append(ModOpReplacePathsWithFunctionBasedPaths(
            "subject_walk_scaled_FunctionBasedPathSet.xml"));
    track.setModel(modelProcessor);

    // Construct a TableProcessor of the coordinate data and pass it to the 
    // tracking tool. TableProcessors can be used in the same way as
    // ModelProcessors by appending TableOperators to modify the base table.
    // A TableProcessor with no operators, as we have here, simply returns the
    // base table.
    track.setStatesReference(TableProcessor("coordinates.sto"));

    // This setting allows extra data columns contained in the states
    // reference that don't correspond to model coordinates.
    track.set_allow_unused_references(true);

    // Since there is only coordinate position data in the states references,
    // this setting is enabled to fill in the missing coordinate speed data
    // using the derivative of splined position data.
    track.set_track_reference_position_derivatives(true);

    // Initial time, final time, and mesh interval.
    track.set_initial_time(0.48);
    track.set_final_time(1.61);
    track.set_mesh_interval(0.02);

    // Instead of calling solve(), call initialize() to receive a pre-configured
    // MocoStudy object based on the settings above. Use this to customize the
    // problem beyond the MocoTrack interface.
    MocoStudy study = track.initialize();

    // Get a reference to the MocoControlGoal that is added to every MocoTrack
    // problem by default.
    MocoProblem& problem = study.updProblem();
    MocoControlGoal& effort =
        dynamic_cast<MocoControlGoal&>(problem.updGoal("control_effort"));
    effort.setWeight(0.1);

    // Put a large weight on the pelvis CoordinateActuators, which act as the
    // residual, or 'hand-of-god', forces which we would like to keep as small
    // as possible.
     Model model = modelProcessor.process();
     for (const auto& coordAct : model.getComponentList<CoordinateActuator>()) {
        auto coordPath = coordAct.getAbsolutePathString();
        if (coordPath.find("pelvis") != std::string::npos) {
            effort.setWeightForControl(coordPath, 10);
        }
    }

    // Constrain the muscle activations at the initial time point to equal
    // the initial muscle excitation value.
    problem.addGoal<MocoInitialActivationGoal>("initial_activation");

    // Update the solver tolerances.
    auto& solver = study.updSolver<MocoCasADiSolver>();
    solver.set_optim_convergence_tolerance(1e-3);
    solver.set_optim_constraint_tolerance(1e-4);
    
    // Solve and visualize.
    MocoSolution solution = study.solve();
    study.visualize(solution);
}

int main() {

    // Solve the torque-driven marker tracking problem.
    torqueDrivenMarkerTracking();

    // Solve the muscle-driven state tracking problem.
    muscleDrivenStateTracking();

    return EXIT_SUCCESS;
}