adam.core.rbd_algorithms

adam.core.rbd_algorithms#

Classes#

RBDAlgorithms

This is a small class that implements Rigid body algorithms retrieving robot quantities, for Floating Base systems - as humanoid robots.

Module Contents#

class adam.core.rbd_algorithms.RBDAlgorithms(model: adam.model.Model, math: adam.core.spatial_math.SpatialMath)[source]#

This is a small class that implements Rigid body algorithms retrieving robot quantities, for Floating Base systems - as humanoid robots.

model[source]#
NDoF[source]#
math[source]#
frame_velocity_representation[source]#
set_frame_velocity_representation(representation: adam.core.constants.Representations)[source]#

Sets the frame velocity representation

Parameters:

representation (str) – The representation of the frame velocity

crba(base_transform: numpy.typing.ArrayLike, joint_positions: numpy.typing.ArrayLike) → numpy.typing.ArrayLike[source]#
This function computes the Composite Rigid body algorithm (Roy Featherstone) that computes the Mass Matrix.

The algorithm is complemented with Orin’s modifications computing the Centroidal Momentum Matrix

Parameters:

  • base_transform (npt.ArrayLike) – The homogenous transform from base to world frame

  • joint_positions (npt.ArrayLike) – The joints position

Returns:

Mass Matrix Jcm (npt.ArrayLike): Centroidal Momentum Matrix

Return type:

M (npt.ArrayLike)

forward_kinematics(frame, base_transform: numpy.typing.ArrayLike, joint_positions: numpy.typing.ArrayLike) → numpy.typing.ArrayLike[source]#

Computes the forward kinematics relative to the specified frame

Parameters:

  • frame (str) – The frame to which the fk will be computed

  • base_transform (npt.ArrayLike) – The homogenous transform from base to world frame

  • joint_positions (npt.ArrayLike) – The joints position

Returns:

The fk represented as Homogenous transformation matrix

Return type:

I_H_L (npt.ArrayLike)

joints_jacobian(frame: str, joint_positions: numpy.typing.ArrayLike) → numpy.typing.ArrayLike[source]#

Returns the Jacobian relative to the specified frame

Parameters:

  • frame (str) – The frame to which the jacobian will be computed

  • base_transform (npt.ArrayLike) – The homogenous transform from base to world frame

  • joint_positions (npt.ArrayLike) – The joints position

Returns:

The Joints Jacobian relative to the frame

Return type:

J (npt.ArrayLike)

jacobian(frame: str, base_transform: numpy.typing.ArrayLike, joint_positions: numpy.typing.ArrayLike) → numpy.typing.ArrayLike[source]#
relative_jacobian(frame: str, joint_positions: numpy.typing.ArrayLike) → numpy.typing.ArrayLike[source]#

Returns the Jacobian between the root link and a specified frame :param frame: The tip of the chain :type frame: str :param joint_positions: The joints position :type joint_positions: npt.ArrayLike

Returns:

The 6 x NDoF Jacobian between the root and the frame

Return type:

J (npt.ArrayLike)

jacobian_dot(frame: str, base_transform: numpy.typing.ArrayLike, joint_positions: numpy.typing.ArrayLike, base_velocity: numpy.typing.ArrayLike, joint_velocities: numpy.typing.ArrayLike) → numpy.typing.ArrayLike[source]#

Returns the Jacobian derivative relative to the specified frame

Parameters:

  • frame (str) – The frame to which the jacobian will be computed

  • base_transform (npt.ArrayLike) – The homogenous transform from base to world frame

  • joint_positions (npt.ArrayLike) – The joints position

  • base_velocity (npt.ArrayLike) – The base velocity

  • joint_velocities (npt.ArrayLike) – The joints velocity

Returns:

The Jacobian derivative relative to the frame

Return type:

J_dot (npt.ArrayLike)

CoM_position(base_transform: numpy.typing.ArrayLike, joint_positions: numpy.typing.ArrayLike) → numpy.typing.ArrayLike[source]#

Returns the CoM position

Parameters:

  • base_transform (T) – The homogenous transform from base to world frame

  • joint_positions (T) – The joints position

Returns:

The CoM position

Return type:

com (T)

CoM_jacobian(base_transform: numpy.typing.ArrayLike, joint_positions: numpy.typing.ArrayLike) → numpy.typing.ArrayLike[source]#

Returns the center of mass (CoM) Jacobian using the centroidal momentum matrix.

Parameters:

  • base_transform (T) – The homogenous transform from base to world frame

  • joint_positions (T) – The joints position

Returns:

The CoM Jacobian

Return type:

J_com (T)

get_total_mass()[source]#

Returns the total mass of the robot

Returns:

The total mass

Return type:

mass

rnea(base_transform: numpy.typing.ArrayLike, joint_positions: numpy.typing.ArrayLike, base_velocity: numpy.typing.ArrayLike, joint_velocities: numpy.typing.ArrayLike, g: numpy.typing.ArrayLike) → numpy.typing.ArrayLike[source]#

Implementation of reduced Recursive Newton-Euler algorithm (no acceleration and external forces). For now used to compute the bias force term

Parameters:

  • frame (str) – The frame to which the jacobian will be computed

  • base_transform (T) – The homogenous transform from base to world frame

  • joint_positions (T) – The joints position

  • base_velocity (T) – The base velocity

  • joint_velocities (T) – The joints velocity

  • g (T) – The 6D gravity acceleration

Returns:

generalized force variables

Return type:

tau (T)

abstractmethod aba()[source]#
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