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%% Part 5: Muscle-driven Inverse Problem with Passive Assistance
% Part 5a: Create a new muscle-driven model, now adding a SpringGeneralizedForce 
% about the knee coordinate.
device = SpringGeneralizedForce('knee_angle_r');
device.setName('spring')
initialstiffness=0;
device.setStiffness(initialstiffness);
device.setRestLength(0);
device.setViscosity(0);
muscleDrivenModel.addForce(device);

newModelFile = 'model_with_knee_device.osim';
muscleDrivenModel.print(newModelFile);

% Add MocoParameter for the knee assistance device parameters 
mypara = MocoParameter('stiffness','/forceset/spring','stiffness',MocoBounds(1,99));
problem.addParameter(mypara);

% Part 5b: Create a ModelProcessor similar to the previous one, using the same
% reserve actuator strength so we can compare muscle activity accurately.
modelProcessor = ModelProcessor(muscleDrivenModel);
modelProcessor.append(ModOpAddReserves(2));
inverse.setModel(modelProcessor);

% Part 5c: Solve! Write solution.
inverseDeviceSolution = inverse.solve();
inverseDeviceSolution.getMocoSolution().write('inverseDeviceSolution.sto');

Code: Select all

%% Part 1: Torque-driven Predictive Problem
% Part 1a: Create a new MocoStudy.
study = MocoStudy();

% Part 1b: Initialize the problem and set the model.
problem = study.updProblem();

% Part 1c: Set bounds on the problem.

% Time bounds
problem.setTimeBounds(0, 1);

% Position bounds: the model should start in a squat and finish 
% standing up.
problem.setStateInfo('/jointset/hip_r/hip_flexion_r/value', ...
    [-2, 0.5], -2, 0);
problem.setStateInfo('/jointset/knee_r/knee_angle_r/value', ...
    [-2, 0], -2, 0);
problem.setStateInfo('/jointset/ankle_r/ankle_angle_r/value', ...
    [-0.5, 0.7], -0.5, 0);

% Velocity bounds: all model coordinates should start and end at rest.
problem.setStateInfoPattern('/jointset/.*/speed', [], 0, 0);

% Part 1d: Add a MocoControlGoal to the problem.
problem.addGoal(MocoControlGoal('myeffort'));


% Add Spring
device = SpringGeneralizedForce('knee_angle_r');
device.setName('spring')
initialstiffness=60;
device.setStiffness(initialstiffness);
device.setRestLength(0);
device.setViscosity(0);
torqueDrivenModel.addForce(device);

%Set Model
problem.setModel(torqueDrivenModel);


% Add MocoParameter for the knee assistance device parameters 
  mypara = MocoParameter('springstiffness','/forceset/spring','stiffness',MocoBounds(49,70));
  problem.addParameter(mypara);

% Part 1e: Configure the solver.
solver = study.initCasADiSolver();
solver.set_num_mesh_intervals(25);
solver.set_optim_convergence_tolerance(1e-4);
solver.set_optim_constraint_tolerance(1e-4);

if ~exist('predictSolution.sto', 'file')
% Part 1f: Solve! Write the solution to file, and visualize.
predictSolution = study.solve();
predictSolution.write('predictSolution.sto');
study.visualize(predictSolution);
end