Add support for segment_actuation_selector

Author: mstoelzle

examples/simulate_tendon_actuated_planar_pcs.py

@@ -44,6 +44,9 @@
 
 # activate all strains (i.e. bending, shear, and axial)
 strain_selector = jnp.ones((3 * num_segments,), dtype=bool)
+# actuation selector for the segments
+segment_actuation_selector = jnp.ones((num_segments,), dtype=bool)
+# segment_actuation_selector = jnp.array([False, True]) # only the last segment is actuated
 
 # define initial configuration
 q0 = jnp.repeat(jnp.array([5.0 * jnp.pi, 0.1, 0.2])[None, :], num_segments, axis=0).flatten()
@@ -99,7 +102,7 @@ def draw_robot(
 
 if __name__ == "__main__":
     strain_basis, forward_kinematics_fn, dynamical_matrices_fn, auxiliary_fns = (
-        planar_pcs.factory(num_segments, sym_exp_filepath, strain_selector)
+        planar_pcs.factory(num_segments, sym_exp_filepath, strain_selector, segment_actuation_selector=segment_actuation_selector)
     )
     actuation_mapping_fn = auxiliary_fns["actuation_mapping_fn"]
     # jit the functions

src/jsrm/systems/tendon_actuated_planar_pcs.py

@@ -24,11 +24,6 @@ def factory(
     if segment_actuation_selector is None:
         segment_actuation_selector = jnp.ones(num_segments, dtype=bool)
 
-    # number of system inputs
-    actuation_dim = segment_actuation_selector.sum()
-    actuation_dim = 2 * num_segments
-    actuation_basis = jnp.eye(actuation_dim)
-
     def actuation_mapping_fn(
         forward_kinematics_fn: Callable,
         jacobian_fn: Callable,
@@ -112,12 +107,17 @@ def compute_A_d_wrt_xi_i(i: Array, l_i: Array, xi_i: Array) -> Array:
 
             return A_sm
 
+        # compute the actuation matrix for all segments
+        # will have shape (num_segments, n_xi, num_segment_tendons)
         A = vmap(compute_actuation_matrix_for_segment, in_axes=(0, 0), out_axes=0)(
             segment_indices, params["d"],
-        ).transpose((1, 0, 2)).reshape(xi.shape[0], -1)
+        )
+        
+        # deactivate the actuation for some segments
+        A = A[segment_actuation_selector]
 
-        # apply the actuation_basis
-        A = A @ actuation_basis
+        # reshape the actuation matrix to have shape (n_xi, n_act)
+        A = A.transpose((1, 0, 2)).reshape(xi.shape[0], -1)
 
         return A