Skip to content

control_utils

Set of utilities for helping to execute robot control

FKSolver

Class for thinly wrapping Lula Forward Kinematics solver

Source code in omnigibson/utils/control_utils.py 
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
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 = pose3_lula.translation

            # get orientation
            rotation_lula = pose3_lula.rotation
            link_orientation = (
                rotation_lula.x(),
                rotation_lula.y(),
                rotation_lula.z(),
                rotation_lula.w(),
            )
            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:

Name Type Description
link_poses dict

Dictionary mapping each robot link name to its pose
Source code in omnigibson/utils/control_utils.py 
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
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 = pose3_lula.translation

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

IKSolver

Class for thinly wrapping Lula IK solver

Source code in omnigibson/utils/control_utils.py 
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
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,
        max_iterations=150,
        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
            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 = np.array(target_pos, dtype=np.float64).reshape(3, 1)
        rot = np.array(T.quat2mat(np.array([0, 0, 0, 1.0]) if target_quat is None else target_quat), dtype=np.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 np.array(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.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 np.array(ik_results.cspace_position)
        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, max_iterations=150, 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
max_iterations int

Number of iterations used for each cyclic coordinate descent.

 150
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/utils/control_utils.py 
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
def solve(
    self,
    target_pos,
    target_quat=None,
    tolerance_pos=0.002,
    tolerance_quat=0.01,
    weight_pos=1.0,
    weight_quat=0.05,
    max_iterations=150,
    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
        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 = np.array(target_pos, dtype=np.float64).reshape(3, 1)
    rot = np.array(T.quat2mat(np.array([0, 0, 0, 1.0]) if target_quat is None else target_quat), dtype=np.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 np.array(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.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 np.array(ik_results.cspace_position)
    else:
        return None

orientation_error(desired, current)

This function calculates a 3-dimensional orientation error vector for use in the impedance controller. It does this by computing the delta rotation between the inputs and converting that rotation to exponential coordinates (axis-angle representation, where the 3d vector is axis * angle). See https://en.wikipedia.org/wiki/Axis%E2%80%93angle_representation for more information. Optimized function to determine orientation error from matrices

Parameters:

Name Type Description Default
desired tensor

(..., 3, 3) where final two dims are 2d array representing target orientation matrix

 required
current tensor

(..., 3, 3) where final two dims are 2d array representing current orientation matrix

 required

Returns: tensor: (..., 3) where final dim is (ax, ay, az) axis-angle representing orientation error

Source code in omnigibson/utils/control_utils.py 
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
@jit(nopython=True)
def orientation_error(desired, current):
    """
    This function calculates a 3-dimensional orientation error vector for use in the
    impedance controller. It does this by computing the delta rotation between the
    inputs and converting that rotation to exponential coordinates (axis-angle
    representation, where the 3d vector is axis * angle).
    See https://en.wikipedia.org/wiki/Axis%E2%80%93angle_representation for more information.
    Optimized function to determine orientation error from matrices

    Args:
        desired (tensor): (..., 3, 3) where final two dims are 2d array representing target orientation matrix
        current (tensor): (..., 3, 3) where final two dims are 2d array representing current orientation matrix
    Returns:
        tensor: (..., 3) where final dim is (ax, ay, az) axis-angle representing orientation error
    """
    # convert input shapes
    input_shape = desired.shape[:-2]
    desired = desired.reshape(-1, 3, 3)
    current = current.reshape(-1, 3, 3)

    # grab relevant info
    rc1 = current[:, :, 0]
    rc2 = current[:, :, 1]
    rc3 = current[:, :, 2]
    rd1 = desired[:, :, 0]
    rd2 = desired[:, :, 1]
    rd3 = desired[:, :, 2]

    error = 0.5 * (np.cross(rc1, rd1) + np.cross(rc2, rd2) + np.cross(rc3, rd3))

    # Reshape
    error = error.reshape(*input_shape, 3)

    return error