"""Wrappers around Pinocchio for easy forward and inverse kinematics."""
import typing
import warnings
import numpy as np
import pinocchio
warnings.warn(
"The pinocchio_utils module has been moved to the robot_properties_fingers package."
" Please update your code accordingly. This version in trifinger_simulation is"
" deprecated and will be removed soon!",
FutureWarning,
stacklevel=1,
)
# === IMPORTANT: This class is deprecated! See warning above.
# The implementation here is kept for now, as robot_properties_fingers is not yet
# pip-installable but should be removed as soon as possible.
# Please do not make any changes here anymore but instead add new features/fixes/etc. in
# robot_properties_fingers.
[docs]
class Kinematics:
"""Forward and inverse kinematics for arbitrary Finger robots.
Provides forward and inverse kinematics functions for a Finger robot with
arbitrarily many independent fingers.
"""
def __init__(
self, finger_urdf_path: str, tip_link_names: typing.Iterable[str]
):
"""
Args:
finger_urdf_path: Path to the URDF file describing the robot.
tip_link_names: Names of the finger tip frames, one per finger.
"""
self.robot_model = pinocchio.buildModelFromUrdf(finger_urdf_path)
self.data = self.robot_model.createData()
self.tip_link_ids = [
self.robot_model.getFrameId(link_name)
for link_name in tip_link_names
]
[docs]
def forward_kinematics(
self,
joint_positions: typing.List[np.ndarray],
joint_velocities: typing.Optional[np.ndarray] = None,
) -> typing.Union[
typing.List[np.ndarray],
typing.Tuple[typing.List[np.ndarray], typing.List[np.ndarray]],
]:
"""Compute end-effector positions (and velocities) for the given joint configuration.
Args:
joint_positions: Flat list of angular joint positions.
joint_velocities: Optional. Flat list of angular joint
velocities.
Returns:
If only joint positions are given: List of end-effector
positions. Each position is given as an np.array with x,y,z
positions.
If joint positions and velocities are given: Tuple with
(i) list of end-effector positions and (ii) list of
end-effector velocities. Each position and velocity is given
as an np.array with x,y,z components.
"""
pinocchio.framesForwardKinematics(
self.robot_model, self.data, joint_positions
)
positions = [
np.asarray(self.data.oMf[link_id].translation).reshape(-1).tolist()
for link_id in self.tip_link_ids
]
if joint_velocities is None:
return positions
else:
pinocchio.forwardKinematics(
self.robot_model, self.data, joint_positions, joint_velocities
)
velocities = []
for link_id in self.tip_link_ids:
local_to_world_transform = pinocchio.SE3.Identity()
local_to_world_transform.rotation = self.data.oMf[
link_id
].rotation
v_local = pinocchio.getFrameVelocity(
self.robot_model, self.data, link_id
)
v_world = local_to_world_transform.act(v_local)
velocities.append(v_world.linear)
return positions, velocities
def _inverse_kinematics_step(
self, frame_id: int, xdes: np.ndarray, q0: np.ndarray
) -> typing.Tuple[np.ndarray, np.ndarray]:
"""Compute one IK iteration for a single finger."""
dt = 1.0e-1
pinocchio.computeJointJacobians(self.robot_model, self.data, q0)
pinocchio.framesForwardKinematics(self.robot_model, self.data, q0)
Ji = pinocchio.getFrameJacobian(
self.robot_model,
self.data,
frame_id,
pinocchio.ReferenceFrame.LOCAL_WORLD_ALIGNED,
)[:3, :]
xcurrent = self.data.oMf[frame_id].translation
try:
Jinv = np.linalg.inv(Ji)
except Exception:
Jinv = np.linalg.pinv(Ji)
err = xdes - xcurrent
dq = Jinv.dot(xdes - xcurrent)
qnext = pinocchio.integrate(self.robot_model, q0, dt * dq)
return qnext, err
[docs]
def inverse_kinematics_one_finger(
self,
finger_idx: int,
tip_target_position: np.ndarray,
joint_angles_guess: np.ndarray,
tolerance: float = 0.005,
max_iterations: int = 1000,
) -> typing.Tuple[np.ndarray, np.ndarray]:
"""Inverse kinematics for a single finger.
Args:
finger_idx: Index of the finger.
tip_target_positions: Target position for the finger tip in world
frame.
joint_angles_guess: Initial guess for the joint angles.
tolerance: Position error tolerance. Stop if the error is less
then that.
max_iterations: Max. number of iterations.
Returns:
First element is the joint configuration (for joints that are not
part of the specified finger, the values from the initial guess are
kept). Second element is (x,y,z)-error of the tip position.
"""
q = joint_angles_guess
for i in range(max_iterations):
q, err = self._inverse_kinematics_step(
self.tip_link_ids[finger_idx], tip_target_position, q
)
if np.linalg.norm(err) < tolerance:
break
return q, err
[docs]
def inverse_kinematics(
self,
tip_target_positions: typing.Iterable[np.ndarray],
joint_angles_guess: np.ndarray,
tolerance: float = 0.005,
max_iterations: int = 1000,
) -> typing.Tuple[np.ndarray, typing.List[np.ndarray]]:
"""Inverse kinematics for the whole manipulator.
Args:
tip_target_positions: List of finger tip target positions, one for
each finger.
joint_angles_guess: See :meth:`inverse_kinematics_one_finger`.
tolerance: See :meth:`inverse_kinematics_one_finger`.
max_iterations: See :meth:`inverse_kinematics_one_finger`.
Returns:
First element is the joint configuration, second element is a list
of (x,y,z)-errors of the tip positions.
"""
q = joint_angles_guess
errors = []
for i, pos in enumerate(tip_target_positions):
q, err = self.inverse_kinematics_one_finger(
i, pos, q, tolerance, max_iterations
)
errors.append(err)
return q, errors