The interpolation between consecutive rotations is performed as a rotation around a fixed axis with a constant angular velocity . This ensures that the interpolated rotations follow the shortest path between initial and final orientations.
Times of the known rotations. At least 2 times must be specified.
Rotations to perform the interpolation between. Must contain N rotations.
Spherical Linear Interpolation of Rotations.
>>> from scipy.spatial.transform import Rotation as R
... from scipy.spatial.transform import Slerp
Setup the fixed keyframe rotations and times:
>>> key_rots = R.random(5, random_state=2342345)
... key_times = [0, 1, 2, 3, 4]
Create the interpolator object:
>>> slerp = Slerp(key_times, key_rots)
Interpolate the rotations at the given times:
>>> times = [0, 0.5, 0.25, 1, 1.5, 2, 2.75, 3, 3.25, 3.60, 4]
... interp_rots = slerp(times)
The keyframe rotations expressed as Euler angles:
>>> key_rots.as_euler('xyz', degrees=True) array([[ 14.31443779, -27.50095894, -3.7275787 ], [ -1.79924227, -24.69421529, 164.57701743], [146.15020772, 43.22849451, -31.34891088], [ 46.39959442, 11.62126073, -45.99719267], [-88.94647804, -49.64400082, -65.80546984]])
The interpolated rotations expressed as Euler angles. These agree with the keyframe rotations at both endpoints of the range of keyframe times.
>>> interp_rots.as_euler('xyz', degrees=True) array([[ 14.31443779, -27.50095894, -3.7275787 ], [ 4.74588574, -32.44683966, 81.25139984], [ 10.71094749, -31.56690154, 38.06896408], [ -1.79924227, -24.69421529, 164.57701743], [ 11.72796022, 51.64207311, -171.7374683 ], [ 146.15020772, 43.22849451, -31.34891088], [ 68.10921869, 20.67625074, -48.74886034], [ 46.39959442, 11.62126073, -45.99719267], [ 12.35552615, 4.21525086, -64.89288124], [ -30.08117143, -19.90769513, -78.98121326], [ -88.94647804, -49.64400082, -65.80546984]])See :
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.spatial.transform._rotation.Slerp
scipy.spatial.transform._rotation.Rotation
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