Dual Quaternion Interpolation#

This example shows interpolated trajectories between two random poses. The red line corresponds to linear interpolation with exponential coordinates, the green line corresponds to linear interpolation with dual quaternions, and the blue line corresponds to screw linear interpolation (ScLERP) with dual quaternions. The true screw motion from pose 1 to pose 2 is shown by a thick, transparent black line in the background of the ScLERP interpolation.

plot dual quaternion interpolation
import numpy as np
import matplotlib.pyplot as plt
import pytransform3d.transformations as pt
import pytransform3d.trajectories as ptr
import pytransform3d.plot_utils as ppu


rng = np.random.default_rng(25)
pose1 = pt.random_transform(rng)
pose2 = pt.random_transform(rng)
dq1 = pt.dual_quaternion_from_transform(pose1)
dq2 = -pt.dual_quaternion_from_transform(pose2)
Stheta1 = pt.exponential_coordinates_from_transform(pose1)
Stheta2 = pt.exponential_coordinates_from_transform(pose2)
pq1 = pt.pq_from_transform(pose1)
pq2 = pt.pq_from_transform(pose2)

n_steps = 100

# Ground truth screw motion: linear interpolation of rotation about and
# translation along the screw axis
pose12pose2 = pt.concat(pose2, pt.invert_transform(pose1))
screw_axis, theta = pt.screw_axis_from_exponential_coordinates(
    pt.exponential_coordinates_from_transform(pose12pose2))
offsets = np.array(
    [pt.transform_from_exponential_coordinates(screw_axis * t * theta)
     for t in np.linspace(0, 1, n_steps)])
interpolated_poses = np.array([
    pt.concat(offset, pose1) for offset in offsets])

# Linear interpolation of dual quaternions
interpolated_dqs = (np.linspace(1, 0, n_steps)[:, np.newaxis] * dq1 +
                    np.linspace(0, 1, n_steps)[:, np.newaxis] * dq2)
# renormalization (not required here because it will be done with conversion)
interpolated_dqs /= np.linalg.norm(
    interpolated_dqs[:, :4], axis=1)[:, np.newaxis]
interpolated_poses_from_dqs = np.array([
    pt.transform_from_dual_quaternion(dq) for dq in interpolated_dqs])

# Screw linear interpolation of dual quaternions (ScLERP)
sclerp_interpolated_dqs = np.vstack([
    pt.dual_quaternion_sclerp(dq1, dq2, t)
    for t in np.linspace(0, 1, n_steps)])
sclerp_interpolated_poses_from_dqs = ptr.transforms_from_dual_quaternions(
    sclerp_interpolated_dqs)

# Linear interpolation of exponential coordinates
interpolated_ecs = (np.linspace(1, 0, n_steps)[:, np.newaxis] * Stheta1 +
                    np.linspace(0, 1, n_steps)[:, np.newaxis] * Stheta2)
interpolates_poses_from_ecs = ptr.transforms_from_exponential_coordinates(
    interpolated_ecs)

# Linear interpolation of position + spherical linear interpolation (SLERP) of
# quaternion
interpolated_pqs = np.vstack([
    pt.pq_slerp(pq1, pq2, t) for t in np.linspace(0, 1, n_steps)])
interpolated_poses_from_pqs = ptr.transforms_from_pqs(interpolated_pqs)

ax = pt.plot_transform(A2B=pose1, s=0.3, ax_s=2)
pt.plot_transform(A2B=pose2, s=0.3, ax=ax)
traj = ppu.Trajectory(
    interpolated_poses, s=0.1, c="k", lw=5, alpha=0.5, show_direction=True)
traj.add_trajectory(ax)
traj_from_dqs = ppu.Trajectory(
    interpolated_poses_from_dqs, s=0.1, c="g", show_direction=False)
traj_from_dqs.add_trajectory(ax)
traj_from_ecs = ppu.Trajectory(
    interpolates_poses_from_ecs, s=0.1, c="r", show_direction=False)
traj_from_ecs.add_trajectory(ax)
traj_from_dqs_sclerp = ppu.Trajectory(
    sclerp_interpolated_poses_from_dqs, s=0.1, c="b", show_direction=False)
traj_from_dqs_sclerp.add_trajectory(ax)
traj_from_pq_slerp = ppu.Trajectory(
    interpolated_poses_from_pqs, s=0.1, c="c", show_direction=False)
traj_from_pq_slerp.add_trajectory(ax)
plt.legend(
    [traj.trajectory, traj_from_dqs.trajectory, traj_from_ecs.trajectory,
     traj_from_dqs_sclerp.trajectory, traj_from_pq_slerp.trajectory],
    ["Screw interpolation", "Linear dual quaternion interpolation",
     "Linear interpolation of exp. coordinates", "Dual quaternion ScLERP",
     "Linear interpolation of position + SLERP of quaternions"],
    loc="best")
plt.show()

Total running time of the script: (0 minutes 0.220 seconds)

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