grasp_synergy.grasp_synergy.GraspSynergy Class Reference

List of all members.

Public Member Functions
def	__init__
def	compute_grasp
def	fit_bag_file
def	fit_joint_state_messages
def	fit_joint_values
def	synergy_range
def	trained
Private Attributes
	_D
	_N
	_pca
	_transformed_joint_angles

---

Detailed Description

A grasp synergy (aka eigengrasp) is a lower-dimensional representation of
the hand configuration useful to simplify all manners of grasping things.

Essentially this is just a utilitarian wrapper around PCA.

Definition at line 17 of file grasp_synergy.py.

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Constructor & Destructor Documentation

def grasp_synergy.grasp_synergy.GraspSynergy.__init__

(

self

)

Definition at line 25 of file grasp_synergy.py.

---

Member Function Documentation

def grasp_synergy.grasp_synergy.GraspSynergy.compute_grasp	(		self,
			alphas
	)

Reconstruct a grasp given a combination of (low-dimensional) synergy
coefficients to get a (full-dimensional) grasp configuration.

The coefficients are a weighting vector of the various (ordered)
principal grasp components.

:return mean + sum_i alpha_i * coeff_i. If the synergy is not already
computed this returns None.

Definition at line 117 of file grasp_synergy.py.

def grasp_synergy.grasp_synergy.GraspSynergy.fit_bag_file	(		self,
			bag_filepath
	)

Extract *all* joint state messages from the given bag file, then
compute the hand synergies.

:param bag_filepath: Fully-qualified filepath of the bagfile.

Definition at line 95 of file grasp_synergy.py.

def grasp_synergy.grasp_synergy.GraspSynergy.fit_joint_state_messages	(		self,
			joint_state_messages
	)

Extract joint state values from a list of ROS messages, then
compute the grasp synergies.

:param joint_state_messages A list of ROS sensor_msgs/JointState.

Definition at line 75 of file grasp_synergy.py.

def grasp_synergy.grasp_synergy.GraspSynergy.fit_joint_values	(		self,
			joint_values
	)

Fit the principal components of the given joint values to compute the
grasp synergies (aka eigengrasps).

We compute and store *all* D principal components here. The
dimensionality of the lower-dimensional subspace is determined at grasp
computation time.

:param joint_values A numpy array (N by D) with N datapoints of D
dimensions.

:return True if the synergies were properly fit.

Definition at line 43 of file grasp_synergy.py.

def grasp_synergy.grasp_synergy.GraspSynergy.synergy_range	(		self,
			component_num
	)

Compute the range of values for the i'th component of the synergy,
using the transformed original values used to train the PCA.

If there are no synergies or the component number is invalid, returns
(0, 0).

:return (min, max) for transformed values

Definition at line 148 of file grasp_synergy.py.

def grasp_synergy.grasp_synergy.GraspSynergy.trained

(

self

)

:return True if the synergy space has been computed.

Definition at line 37 of file grasp_synergy.py.

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Member Data Documentation

grasp_synergy::grasp_synergy.GraspSynergy::_D [private]

Definition at line 25 of file grasp_synergy.py.

grasp_synergy::grasp_synergy.GraspSynergy::_N [private]

Definition at line 25 of file grasp_synergy.py.

grasp_synergy::grasp_synergy.GraspSynergy::_pca [private]

Definition at line 25 of file grasp_synergy.py.

grasp_synergy::grasp_synergy.GraspSynergy::_transformed_joint_angles [private]

Definition at line 25 of file grasp_synergy.py.

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The documentation for this class was generated from the following file:

• grasp_synergy.py