adam.parametric.numpy ===================== .. py:module:: adam.parametric.numpy Submodules ---------- .. toctree:: :maxdepth: 1 /autoapi/adam/parametric/numpy/computations_parametric/index Classes ------- .. autoapisummary:: adam.parametric.numpy.KinDynComputationsParametric Package Contents ---------------- .. py:class:: KinDynComputationsParametric(urdfstring: str, joints_name_list: list, links_name_list: list, root_link: str = None, gravity: numpy.array = np.array([0, 0, -9.80665, 0, 0, 0])) This is a small class that retrieves robot quantities using NumPy for Floating Base systems. This is parametric w.r.t the link length and densities. .. py:attribute:: links_name_list .. py:attribute:: math .. py:attribute:: g .. py:attribute:: urdfstring .. py:attribute:: joints_name_list .. py:attribute:: representation .. py:method:: set_frame_velocity_representation(representation: adam.core.constants.Representations) -> None Sets the representation of the velocity of the frames :param representation: The representation of the velocity :type representation: Representations .. py:method:: mass_matrix(base_transform: numpy.ndarray, joint_positions: numpy.ndarray, length_multiplier: numpy.ndarray, densities: numpy.ndarray) -> numpy.ndarray Returns the Mass Matrix functions computed the CRBA :param base_transform: The homogenous transform from base to world frame :type base_transform: np.ndarray :param joint_positions: The joints position :type joint_positions: np.ndarray :param length_multiplier: The length multiplier of the parametrized links :type length_multiplier: np.ndarray :param densities: The densities of the parametrized links :type densities: np.ndarray :returns: Mass Matrix :rtype: M (np.ndarray) .. py:method:: centroidal_momentum_matrix(base_transform: numpy.ndarray, s: numpy.ndarray, length_multiplier: numpy.ndarray, densities: numpy.ndarray) -> numpy.ndarray Returns the Centroidal Momentum Matrix functions computed the CRBA :param base_transform: The homogenous transform from base to world frame :type base_transform: np.ndarray :param joint_positions: The joint positions :type joint_positions: np.ndarray :param length_multiplier: The length multiplier of the parametrized links :type length_multiplier: np.ndarray :param densities: The densities of the parametrized links :type densities: np.ndarray :returns: Centroidal Momentum matrix :rtype: Jcc (np.ndarray) .. py:method:: forward_kinematics(frame: str, base_transform: numpy.ndarray, joint_positions: numpy.ndarray, length_multiplier: numpy.ndarray, densities: numpy.ndarray) -> numpy.ndarray Computes the forward kinematics relative to the specified frame :param frame: The frame to which the fk will be computed :type frame: str :param base_transform: The homogenous transform from base to world frame :type base_transform: np.ndarray :param joint_positions: The joints position :type joint_positions: np.ndarray :param length_multiplier: The length multiplier of the parametrized links :type length_multiplier: np.ndarray :param densities: The densities of the parametrized links :type densities: np.ndarray :returns: The fk represented as Homogenous transformation matrix :rtype: T_fk (np.ndarray) .. py:method:: jacobian(frame: str, base_transform: numpy.ndarray, joint_positions: numpy.ndarray, length_multiplier: numpy.ndarray, densities: numpy.ndarray) -> numpy.ndarray Returns the Jacobian relative to the specified frame :param frame: The frame to which the jacobian will be computed :type frame: str :param base_transform: The homogenous transform from base to world frame :type base_transform: np.ndarray :param joint_positions: The joints position :type joint_positions: np.ndarray :param length_multiplier: The length multiplier of the parametrized links :type length_multiplier: np.ndarray :param densities: The densities of the parametrized links :type densities: np.ndarray :returns: The Jacobian relative to the frame :rtype: J_tot (np.ndarray) .. py:method:: relative_jacobian(frame: str, joint_positions: numpy.ndarray, length_multiplier: numpy.ndarray, densities: numpy.ndarray) -> numpy.ndarray Returns the Jacobian between the root link and a specified frame frames :param frame: The tip of the chain :type frame: str :param joint_positions: The joints position :type joint_positions: np.ndarray :param length_multiplier: The length multiplier of the parametrized links :type length_multiplier: np.ndarray :param densities: The densities of the parametrized links :type densities: np.ndarray :returns: The Jacobian between the root and the frame :rtype: J (np.ndarray) .. py:method:: jacobian_dot(frame: str, base_transform: numpy.ndarray, joint_positions: numpy.ndarray, base_velocity: numpy.ndarray, joint_velocities: numpy.ndarray, length_multiplier: numpy.ndarray, densities: numpy.ndarray) -> numpy.ndarray Returns the Jacobian derivative relative to the specified frame :param frame: The frame to which the jacobian will be computed :type frame: str :param base_transform: The homogenous transform from base to world frame :type base_transform: np.ndarray :param joint_positions: The joints position :type joint_positions: np.ndarray :param base_velocity: The base velocity :type base_velocity: np.ndarray :param joint_velocities: The joint velocities :type joint_velocities: np.ndarray :param length_multiplier: The length multiplier of the parametrized links :type length_multiplier: np.ndarray :param densities: The densities of the parametrized links :type densities: np.ndarray :returns: The Jacobian derivative relative to the frame :rtype: Jdot (np.ndarray) .. py:method:: CoM_position(base_transform: numpy.ndarray, joint_positions: numpy.ndarray, length_multiplier: numpy.ndarray, densities: numpy.ndarray) -> numpy.ndarray Returns the CoM position :param base_transform: The homogenous transform from base to world frame :type base_transform: np.ndarray :param joint_positions: The joints position :type joint_positions: np.ndarray :param length_multiplier: The length multiplier of the parametrized links :type length_multiplier: np.ndarray :param densities: The densities of the parametrized links :type densities: np.ndarray :returns: The CoM position :rtype: CoM (np.ndarray) .. py:method:: bias_force(base_transform: numpy.ndarray, joint_positions: numpy.ndarray, base_velocity: numpy.ndarray, joint_velocities: numpy.ndarray, length_multiplier: numpy.ndarray, densities: numpy.ndarray) -> numpy.ndarray Returns the bias force of the floating-base dynamics equation, using a reduced RNEA (no acceleration and external forces) :param base_transform: The homogenous transform from base to world frame :type base_transform: np.ndarray :param joint_positions: The joints position :type joint_positions: np.ndarray :param base_velocity: The base velocity :type base_velocity: np.ndarray :param joint_velocities: The joint velocities :type joint_velocities: np.ndarray :param length_multiplier: The length multiplier of the parametrized links :type length_multiplier: np.ndarray :param densities: The densities of the parametrized links :type densities: np.ndarray :returns: the bias force :rtype: h (np.ndarray) .. py:method:: coriolis_term(base_transform: numpy.ndarray, joint_positions: numpy.ndarray, base_velocity: numpy.ndarray, joint_velocities: numpy.ndarray, length_multiplier: numpy.ndarray, densities: numpy.ndarray) -> numpy.ndarray Returns the coriolis term of the floating-base dynamics equation, using a reduced RNEA (no acceleration and external forces) :param base_transform: The homogenous transform from base to world frame :type base_transform: np.ndarray :param joint_positions: The joints position :type joint_positions: np.ndarray :param base_velocity: The base velocity :type base_velocity: np.ndarray :param joint_velocities: The joint velocities :type joint_velocities: np.ndarray :param length_multiplier: The length multiplier of the parametrized links :type length_multiplier: np.ndarray :param densities: The densities of the parametrized links :type densities: np.ndarray :returns: the Coriolis term :rtype: C (np.ndarray) .. py:method:: gravity_term(base_transform: numpy.ndarray, joint_positions: numpy.ndarray, length_multiplier: numpy.ndarray, densities: numpy.ndarray) -> numpy.ndarray Returns the gravity term of the floating-base dynamics equation, using a reduced RNEA (no acceleration and external forces) :param base_transform: The homogenous transform from base to world frame :type base_transform: np.ndarray :param joint_positions: The joints position :type joint_positions: np.ndarray :param length_multiplier: The length multiplier of the parametrized links :type length_multiplier: np.ndarray :param densities: The densities of the parametrized links :type densities: np.ndarray :returns: the gravity term :rtype: G (np.ndarray) .. py:method:: get_total_mass(length_multiplier: numpy.ndarray, densities: numpy.ndarray) -> float Returns the total mass of the robot :param length_multiplier: The length multiplier of the parametrized links :type length_multiplier: np.ndarray :param densities: The densities of the parametrized links :type densities: np.ndarray :returns: The total mass :rtype: mass .. py:method:: get_original_densities() -> list[float] Returns the original densities of the parametric links :returns: The original densities of the parametric links :rtype: densities