The Kinematic B\'ezier Maps. More...

#include <MemoryX/libraries/helpers/KinematicBezierMaps/kbm.h>

Classes
struct	ErrorValuesType
	Return type of the evaluation (KBM::getErrors()) function providing insight in the statistics of the prediction error. More...

Public Types
enum	BBCheckType { INCLUDED = 1 , COVERED = 2 , DISJOINT = 4 , OVERLAPPING = 8 , ALL = 15 }
	Cases for the check of bounding boxes (i.e., an interval $[c_{l,1},c_{u,1}]\times\ldots\times [c_{l,n},c_{u,n}]$ ) and an interval ( $[i_{l,1},i_{u,1}]\times\ldots\times [i_{l,n},i_{u,n}]$ )both in Cartesian coordinates. More...

enum	Optimization { STANDARD , PLS }
	Enum for the preferred optimization method during batch learning. More...

Public Member Functions
void	batch (const Matrix &proprioception, const Matrix &shape, Optimization method=KBM::STANDARD, Real threshold=0.0)
	Implements the batch learning algorithm.

BBCheckType	checkBBox (const Vector &lower, const Vector &upper, Real tolerance=0.0f) const
	Check whether an interval overlaps the the bounding box of the control points.

void	differentiate ()
	Prepares the calculus of the derivatives. Has to be called alwayes after learning.

void	getBBox (Vector &lower, Vector &upper)

Vector	getCenter () const
	Return the center.

Matrix	getControlNet () const

ErrorValuesType	getErrors (const Matrix &proprioception, const Matrix &shape)
	After learning this function gives various error measures over a given test set.online Proprioception must have the same number of columns (i.e., number of samples) while the rows must match the number of input and output dimensions respectively.

Matrix	getJacobian (const Vector &proprioception) const
	Computes the partial derivative with respect to a configuration.

int	getNDim () const

int	getNDoF () const
	Get the number of degrees of freedom (DoF).

Real	getOverlappingVolume (const Vector &lower, const Vector &upper)

Real	getOverlappingVolumeRatio (const Vector &lower, const Vector &upper, Real targetVolume)

Vector	getPartialDerivative (const Vector &proprioception, int iDoF) const
	Computes a partial derivative with respect to a configuration and the specified degree of freedom.

Vector	getSpreadAngles () const
	Return the spread angles.

void	getSubdivisedNet (const Vector newCenter, Vector newSpreadAngles, Matrix &resultingControlNet) const
	Work in progress This method computes the control net of a subdivised KBM instance.

void	getSubdivisedNet (unsigned int dof, Real center, Real newSpreadAngle, Matrix &resultingControlNet) const
	Makes the subdivision only for one degree of freedom.

Real	getVolume ()

	KBM (const KBM &other)
	Copy constructor.

	KBM (int nDoF, int dim, Real spreadAngle)
	Constructor.

void	online (const Matrix &proprioception, const Matrix &shape, Real learnRate=1.0)
	Implements the online learning algorithm.

Matrix	predict (const Matrix &proprioception, int dim=0) const
	Predicts a value of the FK given a set of joint angles.

void	reset ()
	Forgets all previously learned samples.

bool	restore (std::string fileName="")
	loads a KBM with same input/output dimensions from disk (comma-separated values).

void	store (std::string fileName="")
	stores the current KBM as a comma-separated matrix to disk.

void	subdivide (const Vector &center, const Vector &newSpreadAngles)
	Work in progress This method subdivides the KBM representation.

Static Public Member Functions
static BBCheckType	checkBBoxes (const Vector &lower, const Vector &upper, const Matrix &controlNet, Real tolerance=0.0f)
	Check whether an interval overlaps the the bounding box of a given control net.

static KBM_ptr	createFromVirtualRobot (VirtualRobot::KinematicChainPtr chain, VirtualRobot::SceneObjectPtr FoR, const Vector &spreadAngles, bool useOrientation=false)

static KBM_ptr	createKBM (int nDoF, int dim, const Vector &center, const Vector &spreadAngles, const Matrix &controlNet)
	Factory methods.

static void	getBBox (Vector &lower, Vector &upper, const Matrix &controlNet)
	Helper function that extracts the bounding box of a control net.

Detailed Description

The Kinematic B\'ezier Maps.

This class represents the Kinematic B\'ezier Map algorithm. See the unit test on hints on how to use it.

Definition at line 81 of file kbm.h.

Member Enumeration Documentation

◆ BBCheckType

enum BBCheckType

Cases for the check of bounding boxes (i.e., an interval $[c_{l,1},c_{u,1}]\times\ldots\times [c_{l,n},c_{u,n}]$ ) and an interval $i$ ( $[i_{l,1},i_{u,1}]\times\ldots\times [i_{l,n},i_{u,n}]$ )both in Cartesian coordinates.

Enumerator
INCLUDED	The interval is included in the bounding box $\forall j: i_{l,j} > c_{l,j} \wedge c_{u,j} > i_{u,j}$ .
COVERED	The bounding box is covered by the interval $\forall j: i_{l,j} < c_{l,j} \wedge c_{u,j} < i_{u,j}$ (most interesting case for inverse kinematics).
DISJOINT	The bounding box and interval are disjoint $\exists_j: i_{u,j} < c_{l,j} \vee c_{u,j} < i_{l,j}$ .
OVERLAPPING	The interval and bounding box are partially overlapping (if none of the above applies).
ALL

Definition at line 94 of file kbm.h.

◆ Optimization

enum Optimization

Enum for the preferred optimization method during batch learning.

Enumerator
STANDARD
PLS

Definition at line 85 of file kbm.h.

Constructor & Destructor Documentation

◆ KBM() [1/2]

KBM ( const KBM & other )

Copy constructor.

Definition at line 34 of file kbm.cpp.

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◆ KBM() [2/2]

KBM	(	int	nDoF,
		int	dim,
		Real	spreadAngle )

Constructor.

Parameters

nDoF	The number of the kinematic chain's degrees of freedom (number of input dimensions)
dim	The number of output dimensions (usually three)
spreadAngle	The input values should be centered around 0 and this angle should represent their distribution in input space.

Definition at line 46 of file kbm.cpp.

Member Function Documentation

◆ batch()

void batch	(	const Matrix &	proprioception,
		const Matrix &	shape,
		Optimization	method = KBM::STANDARD,
		Real	threshold = 0.0 )

Implements the batch learning algorithm.

Parameters

proprioception	The input values (joint angles)
shape	The output values (e.g. 3D TCP positions)
method	Select optimization with standard linear least mean squares (KBM::STANDARD) or partial least squares (KMB::PLS)
threshold	Models the noise and should equal the expected mean positioning error of the system. Only used with partial least squares (KBM::PLS) Proprioception must have the same number of columns (i.e., number of samples) while the rows must match the number of input and output dimensions respectively.

Definition at line 213 of file kbm.cpp.

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◆ checkBBox()

KBM::BBCheckType checkBBox	(	const Vector &	lower,
		const Vector &	upper,
		Real	tolerance = 0.0f ) const

Check whether an interval overlaps the the bounding box of the control points.

Parameters

lower	The lower bounds of the interval.
upper	The upper bounds of the interval.
tolerance	Widens each bounding box by twice this skalar. You should use lower and upper to implement this behavior regularly.

Definition at line 242 of file inverse.cpp.

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◆ checkBBoxes()

KBM::BBCheckType checkBBoxes	(	const Vector &	lower,
		const Vector &	upper,
		const Matrix &	controlNet,
		Real	tolerance = 0.0f )

static

Check whether an interval overlaps the the bounding box of a given control net.

Parameters

lower	The lower bounds of the interval.
upper	The upper bounds of the interval.
controlNet	Check againt the bounding box of the points defined by the columns of this matrix.
tolerance	Widens each bounding box by twice this skalar. You should use lower and upper to implement this behavior regularly.

See also: KBM::Models::KBM::BBCheckType for details.

Definition at line 248 of file inverse.cpp.

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◆ createFromVirtualRobot()

KBM_ptr createFromVirtualRobot	(	VirtualRobot::KinematicChainPtr	chain,
		VirtualRobot::SceneObjectPtr	FoR,
		const Vector &	spreadAngles,
		bool	useOrientation = false )

static

Definition at line 494 of file kbm.cpp.

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◆ createKBM()

KBM_ptr createKBM	(	int	nDoF,
		int	dim,
		const Vector &	center,
		const Vector &	spreadAngles,
		const Matrix &	controlNet )

static

Factory methods.

Definition at line 455 of file kbm.cpp.

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◆ differentiate()

void differentiate ( )

Prepares the calculus of the derivatives. Has to be called alwayes after learning.

Definition at line 388 of file kbm.cpp.

◆ getBBox() [1/2]

void getBBox	(	Vector &	lower,
		Vector &	upper )

Definition at line 305 of file inverse.cpp.

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◆ getBBox() [2/2]

void getBBox	(	Vector &	lower,
		Vector &	upper,
		const Matrix &	controlNet )

static

Helper function that extracts the bounding box of a control net.

Definition at line 298 of file inverse.cpp.

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◆ getCenter()

Vector getCenter ( ) const

Return the center.

Definition at line 431 of file kbm.cpp.

◆ getControlNet()

Matrix getControlNet ( ) const

Definition at line 449 of file kbm.cpp.

◆ getErrors()

KBM::ErrorValuesType getErrors	(	const Matrix &	proprioception,
		const Matrix &	shape )

After learning this function gives various error measures over a given test set.online Proprioception must have the same number of columns (i.e., number of samples) while the rows must match the number of input and output dimensions respectively.

Definition at line 63 of file kbm.cpp.

◆ getJacobian()

Matrix getJacobian ( const Vector & proprioception ) const

Computes the partial derivative with respect to a configuration.

Definition at line 412 of file kbm.cpp.

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◆ getNDim()

int getNDim ( ) const

Definition at line 443 of file kbm.cpp.

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◆ getNDoF()

int getNDoF ( ) const

Get the number of degrees of freedom (DoF).

Definition at line 437 of file kbm.cpp.

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◆ getOverlappingVolume()

Real getOverlappingVolume	(	const Vector &	lower,
		const Vector &	upper )

Definition at line 327 of file inverse.cpp.

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◆ getOverlappingVolumeRatio()

Real getOverlappingVolumeRatio	(	const Vector &	lower,
		const Vector &	upper,
		Real	targetVolume )

Definition at line 320 of file inverse.cpp.

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◆ getPartialDerivative()

Vector getPartialDerivative	(	const Vector &	proprioception,
		int	iDoF ) const

Computes a partial derivative with respect to a configuration and the specified degree of freedom.

Definition at line 396 of file kbm.cpp.

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◆ getSpreadAngles()

Vector getSpreadAngles ( ) const

Return the spread angles.

Definition at line 425 of file kbm.cpp.

◆ getSubdivisedNet() [1/2]

void getSubdivisedNet	(	const Vector	newCenter,
		Vector	newSpreadAngles,
		Matrix &	resultingControlNet ) const

Work in progress This method computes the control net of a subdivised KBM instance.

Parameters

center	The new zero of the input values.
newSpreadAngles	The new spread angle vector after subdivision.
resultingControlNet	The resulting control net of the subdivised KBM.

This method computes only the control net (i.e., does not create a new KBM instance). It can be used, for instance, in the global inverse kinematics algorithms.

Definition at line 147 of file inverse.cpp.

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◆ getSubdivisedNet() [2/2]

void getSubdivisedNet	(	unsigned int	dof,
		Real	center,
		Real	newSpreadAngle,
		Matrix &	resultingControlNet ) const

Makes the subdivision only for one degree of freedom.

Definition at line 40 of file inverse.cpp.

◆ getVolume()

Real getVolume ( )

Definition at line 311 of file inverse.cpp.

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◆ online()

void online	(	const Matrix &	proprioception,
		const Matrix &	shape,
		Real	learnRate = 1.0 )

Implements the online learning algorithm.

Parameters

proprioception	The input values (joint angles)
shape	The output values (e.g. 3D TCP positions)
learnRate	Learning rate between (0,1) Can be called (and still makes sense) after KBM::restore() and KBM::batch() and prior calls to KBM::online(). Proprioception must have the same number of columns (i.e., number of samples) while the rows must match the number of input and output dimensions respectively.

Definition at line 239 of file kbm.cpp.

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◆ predict()

Matrix predict	(	const Matrix &	proprioception,
		int	dim = 0 ) const

Predicts a value of the FK given a set of joint angles.

Parameters

proprioception	The input values (joint angles in the columns).
dim	If > 0, the prediction assumes it is the last joint in the kinematic chain and creates a coordinate frame according to the partial derivative.

Definition at line 343 of file kbm.cpp.

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◆ reset()

void reset ( )

Forgets all previously learned samples.

Definition at line 329 of file kbm.cpp.

◆ restore()

bool restore ( std::string fileName = "" )

loads a KBM with same input/output dimensions from disk (comma-separated values).

Definition at line 269 of file kbm.cpp.

◆ store()

void store ( std::string fileName = "" )

stores the current KBM as a comma-separated matrix to disk.

Definition at line 469 of file kbm.cpp.

◆ subdivide()

void subdivide	(	const Vector &	center,
		const Vector &	newSpreadAngles )

Work in progress This method subdivides the KBM representation.

Parameters

center	The new zero of the input values.
newSpreadAngles	The new spread angle vector after subdivision. It can also be used to increase the original angles. Important: The new spread angles must be smaller than $90^\circ$ degrees and a smaller value is more suitable in general.

Definition at line 32 of file inverse.cpp.

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

MemoryX/libraries/helpers/KinematicBezierMaps/kbm.h
MemoryX/libraries/helpers/KinematicBezierMaps/inverse.cpp
MemoryX/libraries/helpers/KinematicBezierMaps/kbm.cpp

Classes

Public Types

Public Member Functions

Static Public Member Functions

Detailed Description

Member Enumeration Documentation

◆ BBCheckType

◆ Optimization

Constructor & Destructor Documentation

◆ KBM() [1/2]

◆ KBM() [2/2]

Member Function Documentation

◆ batch()

◆ checkBBox()

◆ checkBBoxes()

◆ createFromVirtualRobot()

◆ createKBM()

◆ differentiate()

◆ getBBox() [1/2]

◆ getBBox() [2/2]

◆ getCenter()

◆ getControlNet()

◆ getErrors()

◆ getJacobian()

◆ getNDim()

◆ getNDoF()

◆ getOverlappingVolume()

◆ getOverlappingVolumeRatio()

◆ getPartialDerivative()

◆ getSpreadAngles()

◆ getSubdivisedNet() [1/2]

◆ getSubdivisedNet() [2/2]

◆ getVolume()

◆ online()

◆ predict()

◆ reset()

◆ restore()

◆ store()

◆ subdivide()