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control_utils

Set of utilities for helping to execute robot control

FKSolver

Class for thinly wrapping Lula Forward Kinematics solver

Source code in OmniGibson/omnigibson/utils/control_utils.py 
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class FKSolver:
    """
    Class for thinly wrapping Lula Forward Kinematics solver
    """

    def __init__(
        self,
        robot_description_path,
        robot_urdf_path,
    ):
        # Create robot description and kinematics
        self.robot_description = lazy.lula.load_robot(robot_description_path, robot_urdf_path)
        self.kinematics = self.robot_description.kinematics()

    def get_link_poses(
        self,
        joint_positions,
        link_names,
    ):
        """
        Given @joint_positions, get poses of the desired links (specified by @link_names)

        Args:
            joint_positions (n-array): Joint positions in configuration space
            link_names (list): List of robot link names we want to specify (e.g. "gripper_link")

        Returns:
            link_poses (dict): Dictionary mapping each robot link name to its pose
        """
        # TODO: Refactor this to go over all links at once
        link_poses = {}
        for link_name in link_names:
            pose3_lula = self.kinematics.pose(joint_positions, link_name)

            # get position
            link_position = th.tensor(pose3_lula.translation, dtype=th.float32)

            # get orientation
            rotation_lula = pose3_lula.rotation
            link_orientation = th.tensor(
                [rotation_lula.x(), rotation_lula.y(), rotation_lula.z(), rotation_lula.w()], dtype=th.float32
            )
            link_poses[link_name] = (link_position, link_orientation)
        return link_poses

Given @joint_positions, get poses of the desired links (specified by @link_names)

Parameters:

Name Type Description Default
joint_positions n - array

Joint positions in configuration space

 required
link_names list

List of robot link names we want to specify (e.g. "gripper_link")

 required

Returns:

Type Description
link_poses (dict

Dictionary mapping each robot link name to its pose
Source code in OmniGibson/omnigibson/utils/control_utils.py 
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def get_link_poses(
    self,
    joint_positions,
    link_names,
):
    """
    Given @joint_positions, get poses of the desired links (specified by @link_names)

    Args:
        joint_positions (n-array): Joint positions in configuration space
        link_names (list): List of robot link names we want to specify (e.g. "gripper_link")

    Returns:
        link_poses (dict): Dictionary mapping each robot link name to its pose
    """
    # TODO: Refactor this to go over all links at once
    link_poses = {}
    for link_name in link_names:
        pose3_lula = self.kinematics.pose(joint_positions, link_name)

        # get position
        link_position = th.tensor(pose3_lula.translation, dtype=th.float32)

        # get orientation
        rotation_lula = pose3_lula.rotation
        link_orientation = th.tensor(
            [rotation_lula.x(), rotation_lula.y(), rotation_lula.z(), rotation_lula.w()], dtype=th.float32
        )
        link_poses[link_name] = (link_position, link_orientation)
    return link_poses

IKSolver

Class for thinly wrapping Lula IK solver

Source code in OmniGibson/omnigibson/utils/control_utils.py 
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class IKSolver:
    """
    Class for thinly wrapping Lula IK solver
    """

    def __init__(
        self,
        robot_description_path,
        robot_urdf_path,
        eef_name,
        reset_joint_pos,
    ):
        # Create robot description, kinematics, and config
        self.robot_description = lazy.lula.load_robot(robot_description_path, robot_urdf_path)
        self.kinematics = self.robot_description.kinematics()
        self.config = lazy.lula.CyclicCoordDescentIkConfig()
        self.eef_name = eef_name
        self.reset_joint_pos = reset_joint_pos

    def solve(
        self,
        target_pos,
        target_quat=None,
        tolerance_pos=0.002,
        tolerance_quat=0.01,
        weight_pos=1.0,
        weight_quat=0.05,
        bfgs_orientation_weight=100.0,
        max_iterations=10,
        initial_joint_pos=None,
    ):
        """
        Backs out joint positions to achieve desired @target_pos and @target_quat

        Args:
            target_pos (3-array): desired (x,y,z) local target cartesian position in robot's base coordinate frame
            target_quat (4-array or None): If specified, desired (x,y,z,w) local target quaternion orientation in
                robot's base coordinate frame. If None, IK will be position-only (will override settings such that
                orientation's tolerance is very high and weight is 0)
            tolerance_pos (float): Maximum position error (L2-norm) for a successful IK solution
            tolerance_quat (float): Maximum orientation error (per-axis L2-norm) for a successful IK solution
            weight_pos (float): Weight for the relative importance of position error during CCD
            weight_quat (float): Weight for the relative importance of position error during CCD
            bfgs_orientation_weight (float): Weight when applying BFGS algorithm during optimization. Only used if
                target_quat is specified
            max_iterations (int): Number of iterations used for each cyclic coordinate descent.
            initial_joint_pos (None or n-array): If specified, will set the initial cspace seed when solving for joint
                positions. Otherwise, will use self.reset_joint_pos

        Returns:
            None or n-array: Joint positions for reaching desired target_pos and target_quat, otherwise None if no
                solution was found
        """
        pos = (
            target_pos.to(th.float64) if isinstance(target_pos, th.Tensor) else th.tensor(target_pos, dtype=th.float64)
        ).reshape(3, 1)

        if target_quat is None:
            rot = T.quat2mat(th.tensor([0, 0, 0, 1.0], dtype=th.float64))
        else:
            rot = T.quat2mat(
                target_quat.to(th.float64)
                if isinstance(target_quat, th.Tensor)
                else th.tensor(target_quat, dtype=th.float64)
            )
        ik_target_pose = lazy.lula.Pose3(lazy.lula.Rotation3(rot), pos)

        # Set the cspace seed and tolerance
        initial_joint_pos = self.reset_joint_pos if initial_joint_pos is None else initial_joint_pos
        self.config.cspace_seeds = [initial_joint_pos]
        self.config.position_tolerance = tolerance_pos
        self.config.orientation_tolerance = 100.0 if target_quat is None else tolerance_quat

        self.config.ccd_position_weight = weight_pos
        self.config.ccd_orientation_weight = 0.0 if target_quat is None else weight_quat
        self.config.bfgs_orientation_weight = 0.0 if target_quat is None else bfgs_orientation_weight
        self.config.max_num_descents = max_iterations

        # Compute target joint positions
        ik_results = lazy.lula.compute_ik_ccd(self.kinematics, ik_target_pose, self.eef_name, self.config)
        if ik_results.success:
            return th.tensor(ik_results.cspace_position, dtype=th.float32)
        else:
            return None

solve(target_pos, target_quat=None, tolerance_pos=0.002, tolerance_quat=0.01, weight_pos=1.0, weight_quat=0.05, bfgs_orientation_weight=100.0, max_iterations=10, initial_joint_pos=None)

Backs out joint positions to achieve desired @target_pos and @target_quat

Parameters:

Name Type Description Default
target_pos 3 - array

desired (x,y,z) local target cartesian position in robot's base coordinate frame

 required
target_quat 4 - array or None

If specified, desired (x,y,z,w) local target quaternion orientation in robot's base coordinate frame. If None, IK will be position-only (will override settings such that orientation's tolerance is very high and weight is 0)

 None
tolerance_pos float

Maximum position error (L2-norm) for a successful IK solution

 0.002
tolerance_quat float

Maximum orientation error (per-axis L2-norm) for a successful IK solution

 0.01
weight_pos float

Weight for the relative importance of position error during CCD

 1.0
weight_quat float

Weight for the relative importance of position error during CCD

 0.05
bfgs_orientation_weight float

Weight when applying BFGS algorithm during optimization. Only used if target_quat is specified

 100.0
max_iterations int

Number of iterations used for each cyclic coordinate descent.

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initial_joint_pos None or n - array

If specified, will set the initial cspace seed when solving for joint positions. Otherwise, will use self.reset_joint_pos

 None

Returns:

Type Description
None or n - array

Joint positions for reaching desired target_pos and target_quat, otherwise None if no solution was found
Source code in OmniGibson/omnigibson/utils/control_utils.py 
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def solve(
    self,
    target_pos,
    target_quat=None,
    tolerance_pos=0.002,
    tolerance_quat=0.01,
    weight_pos=1.0,
    weight_quat=0.05,
    bfgs_orientation_weight=100.0,
    max_iterations=10,
    initial_joint_pos=None,
):
    """
    Backs out joint positions to achieve desired @target_pos and @target_quat

    Args:
        target_pos (3-array): desired (x,y,z) local target cartesian position in robot's base coordinate frame
        target_quat (4-array or None): If specified, desired (x,y,z,w) local target quaternion orientation in
            robot's base coordinate frame. If None, IK will be position-only (will override settings such that
            orientation's tolerance is very high and weight is 0)
        tolerance_pos (float): Maximum position error (L2-norm) for a successful IK solution
        tolerance_quat (float): Maximum orientation error (per-axis L2-norm) for a successful IK solution
        weight_pos (float): Weight for the relative importance of position error during CCD
        weight_quat (float): Weight for the relative importance of position error during CCD
        bfgs_orientation_weight (float): Weight when applying BFGS algorithm during optimization. Only used if
            target_quat is specified
        max_iterations (int): Number of iterations used for each cyclic coordinate descent.
        initial_joint_pos (None or n-array): If specified, will set the initial cspace seed when solving for joint
            positions. Otherwise, will use self.reset_joint_pos

    Returns:
        None or n-array: Joint positions for reaching desired target_pos and target_quat, otherwise None if no
            solution was found
    """
    pos = (
        target_pos.to(th.float64) if isinstance(target_pos, th.Tensor) else th.tensor(target_pos, dtype=th.float64)
    ).reshape(3, 1)

    if target_quat is None:
        rot = T.quat2mat(th.tensor([0, 0, 0, 1.0], dtype=th.float64))
    else:
        rot = T.quat2mat(
            target_quat.to(th.float64)
            if isinstance(target_quat, th.Tensor)
            else th.tensor(target_quat, dtype=th.float64)
        )
    ik_target_pose = lazy.lula.Pose3(lazy.lula.Rotation3(rot), pos)

    # Set the cspace seed and tolerance
    initial_joint_pos = self.reset_joint_pos if initial_joint_pos is None else initial_joint_pos
    self.config.cspace_seeds = [initial_joint_pos]
    self.config.position_tolerance = tolerance_pos
    self.config.orientation_tolerance = 100.0 if target_quat is None else tolerance_quat

    self.config.ccd_position_weight = weight_pos
    self.config.ccd_orientation_weight = 0.0 if target_quat is None else weight_quat
    self.config.bfgs_orientation_weight = 0.0 if target_quat is None else bfgs_orientation_weight
    self.config.max_num_descents = max_iterations

    # Compute target joint positions
    ik_results = lazy.lula.compute_ik_ccd(self.kinematics, ik_target_pose, self.eef_name, self.config)
    if ik_results.success:
        return th.tensor(ik_results.cspace_position, dtype=th.float32)
    else:
        return None