rofunc.learning.ml.tpgmr

1.  Module Contents

1.1.  Classes

TPGMR
TPGMRBi

1.2.  API

class rofunc.learning.ml.tpgmr.TPGMR(demos_x, task_params, nb_states: int = 4, reg: float = 0.001, plot=False)

Bases: rofunc.learning.ml.tpgmm.TPGMM

Initialization

Task-parameterized Gaussian Mixture Regression (TP-GMR) :param demos_x: demo displacement :param task_params: task parameters :param nb_states: number of states in the HMM :param reg: regularization term :param plot: whether to plot the result

gmm_learning()

fit()

reproduce(model, show_demo_idx)

generate(model: pbdlib.HMM, ref_demo_idx: int, task_params: dict) → numpy.ndarray

class rofunc.learning.ml.tpgmr.TPGMRBi(demos_left_x, demos_right_x, task_params, plot=False)

Bases: rofunc.learning.ml.tpgmr.TPGMR

Initialization

Task-parameterized Gaussian Mixture Regression (TP-GMR) :param demos_x: demo displacement :param task_params: task parameters :param nb_states: number of states in the HMM :param reg: regularization term :param plot: whether to plot the result

fit()

reproduce(models, show_demo_idx)

generate(models, ref_demo_idx: int, task_params: dict) → Tuple[numpy.ndarray, numpy.ndarray]