pytransform3d.transformations.random_transform#

pytransform3d.transformations.random_transform(rng=Generator(PCG64) at 0x7F2FD964C580, mean=array([[1., 0., 0., 0.],        [0., 1., 0., 0.],        [0., 0., 1., 0.],        [0., 0., 0., 1.]]), cov=array([[1., 0., 0., 0., 0., 0.],        [0., 1., 0., 0., 0., 0.],        [0., 0., 1., 0., 0., 0.],        [0., 0., 0., 1., 0., 0.],        [0., 0., 0., 0., 1., 0.],        [0., 0., 0., 0., 0., 1.]]))[source]#

Generate random transform.

Generate \(\Delta \boldsymbol{T}_{B_{i+1}{B_i}} \boldsymbol{T}_{{B_i}A}\), with \(\Delta \boldsymbol{T}_{B_{i+1}{B_i}} = Exp(S \theta)\) and \(\mathcal{S}\theta \sim \mathcal{N}(\boldsymbol{0}_6, \boldsymbol{\Sigma}_{6 \times 6})\). The mean \(\boldsymbol{T}_{{B_i}A}\) and the covariance \(\boldsymbol{\Sigma}_{6 \times 6}\) are parameters of the function.

Note that uncertainty is defined in the global frame B, not in the body frame A.

Parameters:
rngnp.random.Generator, optional (default: random seed 0)

Random number generator

meanarray-like, shape (4, 4), optional (default: I)

Mean transform as homogeneous transformation matrix.

covarray-like, shape (6, 6), optional (default: I)

Covariance of noise in exponential coordinate space.

Returns:
A2Barray-like, shape (4, 4)

Random transform from frame A to frame B

Examples using pytransform3d.transformations.random_transform#

Sample Transforms

Sample Transforms

Plot with Respect to Different Reference Frames

Plot with Respect to Different Reference Frames

Invert Uncertain Transform

Invert Uncertain Transform

Plot Random Geometries

Plot Random Geometries

Dual Quaternion Interpolation

Dual Quaternion Interpolation