Finalize the functional APIs and replace the OOP classes

.github/workflows/ci_cd.yml

@@ -100,11 +100,22 @@ jobs:
         with:
           fetch-depth: 0
 
-      - name: Install Gazebo Classic
+#      - name: Install Gazebo Classic
+#        if: contains(matrix.os, 'ubuntu')
+#        run: |
+#          sudo apt-get update
+#          sudo apt-get install gazebo
+
+      # https://gazebosim.org/docs/harmonic/install_ubuntu
+      - name: Install Gazebo Sim
         if: contains(matrix.os, 'ubuntu')
         run: |
           sudo apt-get update
-          sudo apt-get install gazebo
+          sudo apt-get install lsb-release wget gnupg
+          sudo wget https://packages.osrfoundation.org/gazebo.gpg -O /usr/share/keyrings/pkgs-osrf-archive-keyring.gpg
+          echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/pkgs-osrf-archive-keyring.gpg] http://packages.osrfoundation.org/gazebo/ubuntu-stable $(lsb_release -cs) main" | sudo tee /etc/apt/sources.list.d/gazebo-stable.list > /dev/null
+          sudo apt-get update
+          sudo apt-get install gz-harmonic
 
       - name: Run the Python tests
         if: contains(matrix.os, 'ubuntu')

environment.yml

@@ -10,7 +10,7 @@ dependencies:
   - jaxlie >= 1.3.0
   - jax-dataclasses >= 1.4.0
   - pptree
-  - rod
+  - rod >= 0.2.0
   - typing_extensions # python<3.12
   # Optional dependencies from setup.cfg
   # [style]
@@ -19,7 +19,6 @@ dependencies:
   # [testing]
   - idyntree
   - pytest
-  - pytest-forked
   - pytest-icdiff
   - robot_descriptions
   # [viz]

pyproject.toml

@@ -19,7 +19,7 @@ multi_line_output = 3
 
 [tool.pytest.ini_options]
 minversion = "6.0"
-addopts = "-rsxX -v --strict-markers --forked"
+addopts = "-rsxX -v --strict-markers"
 testpaths = [
     "tests",
 ]

setup.cfg

@@ -53,12 +53,12 @@ package_dir =
 python_requires = >=3.11
 install_requires =
     coloredlogs
-    jax >= 0.4.13,< 0.4.25
-    jaxlib >= 0.4.13,< 0.4.25
+    jax >= 0.4.13
+    jaxlib >= 0.4.13
     jaxlie >= 1.3.0
     jax_dataclasses >= 1.4.0
     pptree
-    rod
+    rod >= 0.2.0
     typing_extensions ; python_version < '3.12'
 
 [options.packages.find]
@@ -71,8 +71,7 @@ style =
     pre-commit
 testing =
     idyntree
-    pytest >= 6.0
-    pytest-forked
+    pytest >=6.0
     pytest-icdiff
     robot-descriptions
 viz =

src/jaxsim/__init__.py

@@ -61,7 +61,6 @@ def _is_editable() -> bool:
 del _np_options
 del _is_editable
 
-from . import high_level, logging, math, simulation, sixd
-from .high_level.common import VelRepr
-from .simulation.ode_integration import IntegratorType
-from .simulation.simulator import JaxSim
+from . import terrain  # isort:skip
+from . import api, integrators, logging, math, rbda
+from .api.common import VelRepr

src/jaxsim/api/__init__.py

@@ -1 +1,3 @@
-from . import contact, data, joint, link, model, ode
+from . import common  # isort:skip
+from . import model, data  # isort:skip
+from . import com, contact, joint, kin_dyn_parameters, link, ode, ode_data, references

src/jaxsim/api/com.py

@@ -0,0 +1,240 @@
+import jax
+import jax.numpy as jnp
+import jaxlie
+
+import jaxsim.api as js
+import jaxsim.math
+import jaxsim.typing as jtp
+
+from .common import VelRepr
+
+
+@jax.jit
+def com_position(
+    model: js.model.JaxSimModel, data: js.data.JaxSimModelData
+) -> jtp.Vector:
+    """
+    Compute the position of the center of mass of the model.
+
+    Args:
+        model: The model to consider.
+        data: The data of the considered model.
+
+    Returns:
+        The position of the center of mass of the model w.r.t. the world frame.
+    """
+
+    m = js.model.total_mass(model=model)
+
+    W_H_L = js.model.forward_kinematics(model=model, data=data)
+    W_H_B = data.base_transform()
+    B_H_W = jaxlie.SE3.from_matrix(W_H_B).inverse().as_matrix()
+
+    def B_p̃_LCoM(i) -> jtp.Vector:
+        m = js.link.mass(model=model, link_index=i)
+        L_p_LCoM = js.link.com_position(
+            model=model, data=data, link_index=i, in_link_frame=True
+        )
+        return m * B_H_W @ W_H_L[i] @ jnp.hstack([L_p_LCoM, 1])
+
+    com_links = jax.vmap(B_p̃_LCoM)(jnp.arange(model.number_of_links()))
+
+    B_p̃_CoM = (1 / m) * com_links.sum(axis=0)
+    B_p̃_CoM = B_p̃_CoM.at[3].set(1)
+
+    return (W_H_B @ B_p̃_CoM)[0:3].astype(float)
+
+
+@jax.jit
+def com_linear_velocity(
+    model: js.model.JaxSimModel, data: js.data.JaxSimModelData
+) -> jtp.Vector:
+    r"""
+    Compute the linear velocity of the center of mass of the model.
+
+    Args:
+        model: The model to consider.
+        data: The data of the considered model.
+
+    Returns:
+        The linear velocity of the center of mass of the model in the
+        active representation.
+
+    Note:
+        The linear velocity of the center of mass  is expressed in the mixed frame
+        :math:`G = ({}^W \mathbf{p}_{\text{CoM}}, [C])`, where :math:`[C] = [W]` if the
+        active velocity representation is either inertial-fixed or mixed,
+        and :math:`[C] = [B]` if the active velocity representation is body-fixed.
+    """
+
+    # Extract the linear component of the 6D average centroidal velocity.
+    # This is expressed in G[B] in body-fixed representation, and in G[W] in
+    # inertial-fixed or mixed representation.
+    G_vl_WG = average_centroidal_velocity(model=model, data=data)[0:3]
+
+    return G_vl_WG
+
+
+@jax.jit
+def centroidal_momentum(
+    model: js.model.JaxSimModel, data: js.data.JaxSimModelData
+) -> jtp.Vector:
+    r"""
+    Compute the centroidal momentum of the model.
+
+    Args:
+        model: The model to consider.
+        data: The data of the considered model.
+
+    Returns:
+        The centroidal momentum of the model.
+
+    Note:
+        The centroidal momentum is expressed in the mixed frame
+        :math:`({}^W \mathbf{p}_{\text{CoM}}, [C])`, where :math:`C = W` if the
+        active velocity representation is either inertial-fixed or mixed,
+        and :math:`C = B` if the active velocity representation is body-fixed.
+    """
+
+    ν = data.generalized_velocity()
+    G_J = centroidal_momentum_jacobian(model=model, data=data)
+
+    return G_J @ ν
+
+
+@jax.jit
+def centroidal_momentum_jacobian(
+    model: js.model.JaxSimModel, data: js.data.JaxSimModelData
+) -> jtp.Matrix:
+    r"""
+    Compute the Jacobian of the centroidal momentum of the model.
+
+    Args:
+        model: The model to consider.
+        data: The data of the considered model.
+
+    Returns:
+        The Jacobian of the centroidal momentum of the model.
+
+    Note:
+        The frame corresponding to the output representation of this Jacobian is either
+        :math:`G[W]`, if the active velocity representation is inertial-fixed or mixed,
+        or :math:`G[B]`, if the active velocity representation is body-fixed.
+
+    Note:
+        This Jacobian is also known in the literature as Centroidal Momentum Matrix.
+    """
+
+    # Compute the Jacobian of the total momentum with body-fixed output representation.
+    # We convert the output representation either to G[W] or G[B] below.
+    B_Jh = js.model.total_momentum_jacobian(
+        model=model, data=data, output_vel_repr=VelRepr.Body
+    )
+
+    W_H_B = data.base_transform()
+    B_H_W = jaxsim.math.Transform.inverse(W_H_B)
+
+    W_p_CoM = com_position(model=model, data=data)
+
+    match data.velocity_representation:
+        case VelRepr.Inertial | VelRepr.Mixed:
+            W_H_G = W_H_GW = jnp.eye(4).at[0:3, 3].set(W_p_CoM)
+        case VelRepr.Body:
+            W_H_G = W_H_GB = W_H_B.at[0:3, 3].set(W_p_CoM)
+        case _:
+            raise ValueError(data.velocity_representation)
+
+    # Compute the transform for 6D forces.
+    G_Xf_B = jaxsim.math.Adjoint.from_transform(transform=B_H_W @ W_H_G).T
+
+    return G_Xf_B @ B_Jh
+
+
+@jax.jit
+def locked_centroidal_spatial_inertia(
+    model: js.model.JaxSimModel, data: js.data.JaxSimModelData
+):
+    """
+    Compute the locked centroidal spatial inertia of the model.
+
+    Args:
+        model: The model to consider.
+        data: The data of the considered model.
+
+    Returns:
+        The locked centroidal spatial inertia of the model.
+    """
+
+    with data.switch_velocity_representation(VelRepr.Body):
+        B_Mbb_B = js.model.locked_spatial_inertia(model=model, data=data)
+
+    W_H_B = data.base_transform()
+    W_p_CoM = com_position(model=model, data=data)
+
+    match data.velocity_representation:
+        case VelRepr.Inertial | VelRepr.Mixed:
+            W_H_G = W_H_GW = jnp.eye(4).at[0:3, 3].set(W_p_CoM)
+        case VelRepr.Body:
+            W_H_G = W_H_GB = W_H_B.at[0:3, 3].set(W_p_CoM)
+        case _:
+            raise ValueError(data.velocity_representation)
+
+    B_H_G = jaxlie.SE3.from_matrix(jaxsim.math.Transform.inverse(W_H_B) @ W_H_G)
+
+    B_Xv_G = B_H_G.adjoint()
+    G_Xf_B = B_Xv_G.transpose()
+
+    return G_Xf_B @ B_Mbb_B @ B_Xv_G
+
+
+@jax.jit
+def average_centroidal_velocity(
+    model: js.model.JaxSimModel, data: js.data.JaxSimModelData
+) -> jtp.Vector:
+    r"""
+    Compute the average centroidal velocity of the model.
+
+    Args:
+        model: The model to consider.
+        data: The data of the considered model.
+
+    Returns:
+        The average centroidal velocity of the model.
+
+    Note:
+        The average velocity is expressed in the mixed frame
+        :math:`G = ({}^W \mathbf{p}_{\text{CoM}}, [C])`, where :math:`[C] = [W]` if the
+        active velocity representation is either inertial-fixed or mixed,
+        and :math:`[C] = [B]` if the active velocity representation is body-fixed.
+    """
+
+    ν = data.generalized_velocity()
+    G_J = average_centroidal_velocity_jacobian(model=model, data=data)
+
+    return G_J @ ν
+
+
+@jax.jit
+def average_centroidal_velocity_jacobian(
+    model: js.model.JaxSimModel, data: js.data.JaxSimModelData
+) -> jtp.Matrix:
+    r"""
+    Compute the Jacobian of the average centroidal velocity of the model.
+
+    Args:
+        model: The model to consider.
+        data: The data of the considered model.
+
+    Returns:
+        The Jacobian of the average centroidal velocity of the model.
+
+    Note:
+        The frame corresponding to the output representation of this Jacobian is either
+        :math:`G[W]`, if the active velocity representation is inertial-fixed or mixed,
+        or :math:`G[B]`, if the active velocity representation is body-fixed.
+    """
+
+    G_J = centroidal_momentum_jacobian(model=model, data=data)
+    G_Mbb = locked_centroidal_spatial_inertia(model=model, data=data)
+
+    return jnp.linalg.inv(G_Mbb) @ G_J

src/jaxsim/api/common.py

@@ -1,6 +1,7 @@
 import abc
 import contextlib
 import dataclasses
+import enum
 import functools
 from typing import ContextManager
 
@@ -11,7 +12,6 @@
 from jax_dataclasses import Static
 
 import jaxsim.typing as jtp
-from jaxsim.high_level.common import VelRepr
 from jaxsim.utils import JaxsimDataclass, Mutability
 
 try:
@@ -20,6 +20,17 @@
     from typing_extensions import Self
 
 
+@enum.unique
+class VelRepr(enum.IntEnum):
+    """
+    Enumeration of all supported 6D velocity representations.
+    """
+
+    Body = enum.auto()
+    Mixed = enum.auto()
+    Inertial = enum.auto()
+
+
 @jax_dataclasses.pytree_dataclass
 class ModelDataWithVelocityRepresentation(JaxsimDataclass, abc.ABC):
     """
@@ -59,7 +70,7 @@ def switch_velocity_representation(
             # We run this in a mutable context with restoration so that any exception
             # occurring, we restore the original object in case it was modified.
             with self.mutable_context(
-                mutability=self._mutability(), restore_after_exception=True
+                mutability=self.mutability(), restore_after_exception=True
             ):
                 yield self