Allow models with a single link in RBDAs with JAX_DISABLE_JIT

src/jaxsim/rbda/crba.py

@@ -59,10 +59,14 @@ def propagate_kinematics(
 
         return (i_X_0,), None
 
-    (i_X_0,), _ = jax.lax.scan(
-        f=propagate_kinematics,
-        init=forward_pass_carry,
-        xs=jnp.arange(start=1, stop=model.number_of_links()),
+    (i_X_0,), _ = (
+        jax.lax.scan(
+            f=propagate_kinematics,
+            init=forward_pass_carry,
+            xs=jnp.arange(start=1, stop=model.number_of_links()),
+        )
+        if model.number_of_links() > 1
+        else [(i_X_0,), None]
     )
 
     # ===================
@@ -128,10 +132,21 @@ def compute_inner(carry: CarryInnerFn) -> tuple[CarryInnerFn, None]:
                 operand=carry,
             )
 
-        (j, Fi, M), _ = jax.lax.scan(
-            f=inner_fn,
-            init=carry_inner_fn,
-            xs=jnp.flip(jnp.arange(start=1, stop=model.number_of_links())),
+        (j, Fi, M), _ = (
+            jax.lax.scan(
+                f=inner_fn,
+                init=carry_inner_fn,
+                xs=jnp.flip(jnp.arange(start=1, stop=model.number_of_links())),
+            )
+            if model.number_of_links() > 1
+            else [
+                (
+                    j,
+                    Fi,
+                    M,
+                ),
+                None,
+            ]
         )
 
         Fi = i_X_0[j].T @ Fi
@@ -143,10 +158,14 @@ def compute_inner(carry: CarryInnerFn) -> tuple[CarryInnerFn, None]:
 
     # This scan performs the backward pass to compute Mbj, Mjb and Mjj, that
     # also includes a fake while loop implemented with a scan and two cond.
-    (Mc, M), _ = jax.lax.scan(
-        f=backward_pass,
-        init=backward_pass_carry,
-        xs=jnp.flip(jnp.arange(start=1, stop=model.number_of_links())),
+    (Mc, M), _ = (
+        jax.lax.scan(
+            f=backward_pass,
+            init=backward_pass_carry,
+            xs=jnp.flip(jnp.arange(start=1, stop=model.number_of_links())),
+        )
+        if model.number_of_links() > 1
+        else [(Mc, M), None]
     )
 
     # Store the locked 6D rigid-body inertia matrix Mbb ∈ ℝ⁶ˣ⁶.

src/jaxsim/rbda/forward_kinematics.py

@@ -75,10 +75,14 @@ def propagate_kinematics(
 
         return (W_X_i,), None
 
-    (W_X_i,), _ = jax.lax.scan(
-        f=propagate_kinematics,
-        init=propagate_kinematics_carry,
-        xs=jnp.arange(start=1, stop=model.number_of_links()),
+    (W_X_i,), _ = (
+        jax.lax.scan(
+            f=propagate_kinematics,
+            init=propagate_kinematics_carry,
+            xs=jnp.arange(start=1, stop=model.number_of_links()),
+        )
+        if model.number_of_links() > 1
+        else [(W_X_i,), None]
     )
 
     return jax.vmap(Adjoint.to_transform)(W_X_i)

src/jaxsim/rbda/jacobian.py

@@ -67,10 +67,14 @@ def propagate_kinematics(
 
         return (i_X_0,), None
 
-    (i_X_0,), _ = jax.lax.scan(
-        f=propagate_kinematics,
-        init=propagate_kinematics_carry,
-        xs=np.arange(start=1, stop=model.number_of_links()),
+    (i_X_0,), _ = (
+        jax.lax.scan(
+            f=propagate_kinematics,
+            init=propagate_kinematics_carry,
+            xs=np.arange(start=1, stop=model.number_of_links()),
+        )
+        if model.number_of_links() > 1
+        else [(i_X_0,), None]
     )
 
     # ============================
@@ -105,10 +109,14 @@ def update_jacobian(J: jtp.Matrix, i: jtp.Int) -> jtp.Matrix:
 
         return J, None
 
-    L_J_WL_B, _ = jax.lax.scan(
-        f=compute_jacobian,
-        init=J,
-        xs=np.arange(start=1, stop=model.number_of_links()),
+    L_J_WL_B, _ = (
+        jax.lax.scan(
+            f=compute_jacobian,
+            init=J,
+            xs=np.arange(start=1, stop=model.number_of_links()),
+        )
+        if model.number_of_links() > 1
+        else [J, None]
     )
 
     return L_J_WL_B
@@ -184,10 +192,14 @@ def compute_full_jacobian(
 
         return (B_X_i, J), None
 
-    (B_X_i, J), _ = jax.lax.scan(
-        f=compute_full_jacobian,
-        init=compute_full_jacobian_carry,
-        xs=np.arange(start=1, stop=model.number_of_links()),
+    (B_X_i, J), _ = (
+        jax.lax.scan(
+            f=compute_full_jacobian,
+            init=compute_full_jacobian_carry,
+            xs=np.arange(start=1, stop=model.number_of_links()),
+        )
+        if model.number_of_links() > 1
+        else [(B_X_i, J), None]
     )
 
     # Convert adjoints to SE(3) transforms.