Package org.robwork.sdurw_pathoptimization

Class PathLengthOptimizerPtr

java.lang.Object

org.robwork.sdurw_pathoptimization.PathLengthOptimizerPtr

public class PathLengthOptimizerPtr
extends java.lang.Object

Ptr stores a pointer and optionally takes ownership of the value.

Constructor Summary

Constructors

Constructor	Description
PathLengthOptimizerPtr()	Default constructor yielding a NULL-pointer.
PathLengthOptimizerPtr(long cPtr, boolean cMemoryOwn)
PathLengthOptimizerPtr(PathLengthOptimizer ptr)	Do not take ownership of ptr. ptr can be null. The constructor is implicit on purpose.

Method Summary

Modifier and Type	Method	Description
PathLengthOptimizer	__ref__()	Dereferencing operator.
PathLengthOptimizerCPtr	cptr()
void	delete()
PathLengthOptimizer	deref()	The pointer stored in the object.
boolean	equals(PathLengthOptimizer p)
static long	getCPtr(PathLengthOptimizerPtr obj)
PathLengthOptimizer	getDeref()	Member access operator.
java.lang.String	getPROP_LOOPCOUNT()	Property key for the maximal number of loops
java.lang.String	getPROP_MAXTIME()	Property key for max time
java.lang.String	getPROP_SUBDIVLENGTH()	Property key for length of segment in when subdividing
PropertyMap	getPropertyMap()	Returns the propertymap
boolean	isNull()	checks if the pointer is null
boolean	isShared()	check if this Ptr has shared ownership or none ownership
SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t	partialShortCut(SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t path)	Optimizes using the partial shortcut technique Works similar to partialShortCut(const rw::pathplanning::Path&, size_t, double, double) except that parameters are read from the propertymap.
SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t	partialShortCut(SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t path, long cnt, double time, double subDivideLength)	Optimizes using the partial shortcut technique The partialShortCut algorithm select two random node indices i and j and a random position in the configuration vector.
SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t	pathPruning(SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t path)	Optimizes using path pruning. pathPruning runs through the path an tests if nodes with index i and i+2 can be directly connected.
SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t	shortCut(SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t path)	Optimizes using the shortcut technique Works similar to shortCut(const rw::pathplanning::Path&, size_t, double, double) except that parameters are read from the propertymap.
SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t	shortCut(SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t path, long cnt, double time, double subDivideLength)	Optimizes using the shortcut technique The shortCut algorithm works by selecting two random indices i and j and try to connect those. The algorithm will loop until either the specified cnt is of met or the specified time is reached.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

PathLengthOptimizerPtr

public PathLengthOptimizerPtr(long cPtr,
                              boolean cMemoryOwn)

PathLengthOptimizerPtr

public PathLengthOptimizerPtr()

Default constructor yielding a NULL-pointer.

PathLengthOptimizerPtr

public PathLengthOptimizerPtr(PathLengthOptimizer ptr)

Do not take ownership of ptr.

ptr can be null.

The constructor is implicit on purpose.

Method Detail

getCPtr

public static long getCPtr(PathLengthOptimizerPtr obj)

delete

public void delete()

deref

public PathLengthOptimizer deref()

The pointer stored in the object.

__ref__

public PathLengthOptimizer __ref__()

Dereferencing operator.

getDeref

public PathLengthOptimizer getDeref()

Member access operator.

equals

public boolean equals(PathLengthOptimizer p)

isShared

public boolean isShared()

check if this Ptr has shared ownership or none
ownership

Returns:

true if Ptr has shared ownership, false if it has no ownership.

isNull

public boolean isNull()

checks if the pointer is null

Returns:

Returns true if the pointer is null

cptr

public PathLengthOptimizerCPtr cptr()

pathPruning

public SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t pathPruning(SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t path)

Optimizes using path pruning.

pathPruning runs through the path an tests if nodes with
index i and i+2 can be directly connected. If so it removes node i+1.

Parameters:

path - [in] Path to optimize

shortCut

public SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t shortCut(SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t path,
                                                               long cnt,
                                                               double time,
                                                               double subDivideLength)

Optimizes using the shortcut technique

The shortCut algorithm works by selecting two random indices i and j and
try to connect those.

The algorithm will loop until either the specified cnt is of met or the specified
time is reached.

Parameters:

path - [inout] Path to optimize

cnt - [in] Max count to use. If cnt=0, only the time limit will be used

time - [in] Max time to use (in seconds). If time=0, only the cnt limit will be used

subDivideLength - [in] The length into which the path is subdivided

shortCut

public SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t shortCut(SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t path)

Optimizes using the shortcut technique

Works similar to shortCut(const rw::pathplanning::Path&, size_t,
double, double) except that parameters are read from the propertymap.

Parameters:

path - [inout] Path to optimize

partialShortCut

public SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t partialShortCut(SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t path,
                                                                      long cnt,
                                                                      double time,
                                                                      double subDivideLength)

Optimizes using the partial shortcut technique

The partialShortCut algorithm select two random node indices i and j and a random
position in the configuration vector. A shortcut is then only tried between the values
corresponding to the random position.

The algorithm will loop until either the specified cnt is of met or the specified
time is reached.

Parameters:

path - [inout] Path to optimize

cnt - [in] Max count to use. If cnt=0, only the time limit will be used

time - [in] Max time to use (in seconds). If time=0, only the cnt limit will be used

subDivideLength - [in] The length into which the path is subdivided

partialShortCut

public SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t partialShortCut(SWIGTYPE_p_rw__trajectory__PathT_rw__math__Q_t path)

Optimizes using the partial shortcut technique

Works similar to partialShortCut(const rw::pathplanning::Path&,
size_t, double, double) except that parameters are read from the
propertymap.

Parameters:

path - [inout] Path to optimize

Returns:

The optimized path

getPropertyMap

public PropertyMap getPropertyMap()

Returns the propertymap

Returns:

Reference to the property map

getPROP_LOOPCOUNT

public java.lang.String getPROP_LOOPCOUNT()

Property key for the maximal number of loops

getPROP_MAXTIME

public java.lang.String getPROP_MAXTIME()

Property key for max time

getPROP_SUBDIVLENGTH

public java.lang.String getPROP_SUBDIVLENGTH()

Property key for length of segment in when subdividing