Skip to content

[RTR] implicit defect works in torque driven. #515

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
pariterre merged 2 commits into from
Aug 11, 2022
Merged

[RTR] implicit defect works in torque driven. #515

Changes from 1 commit
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
20547e4
implicit defect works in torque driven.
Ipuch Aug 10, 2022
203366a
Ipuch Aug 11, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 2 additions & 4 deletions bioptim/dynamics/dynamics_functions.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -155,9 +155,7 @@ def torque_driven(
)
)
defects[: dq.shape[0], :] = horzcat(*dq_defects)

tau_var = nlp.states["tau"] if "tau" in nlp.states else nlp.controls["tau"]
defects[dq.shape[0] :, :] = tau_var.mapping.to_first.map(tau) - tau_id
defects[dq.shape[0]:, :] = tau - tau_id

return DynamicsEvaluation(dxdt, defects)

Expand Down Expand Up @@ -639,7 +637,7 @@ def inverse_dynamics(
tau[:, i] = nlp.model.InverseDynamics(q, qdot, qddot, f_ext).to_mx()
else:
tau = nlp.model.InverseDynamics(q, qdot, qddot).to_mx()
return tau_var.mapping.to_first.map(tau)
return tau

@staticmethod
def compute_muscle_dot(nlp: NonLinearProgram, muscle_excitations: Union[MX, SX]):
Expand Down