Package org.robwork.sdurw_pathoptimization

Class PathLengthOptimizer

java.lang.Object

org.robwork.sdurw_pathoptimization.PathLengthOptimizer

public class PathLengthOptimizer
extends java.lang.Object

The PathLengthOptimizer implements the 3 different path length optimizers
presented in [1].

[1]: R. Geraerts and M.H. Overmars, Creating High-Quality Paths for Motion Planning,
The International Journal of Robotics Research, Vol. 26, No. 8, 845-863 (2007)

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

The shortCut algorithm works similary except that it takes two random indices
i and j and tries to connect those. This algorithm is non-deterministic but more
powerful than pathPruning.

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. This algorithm is generally more powerful than
shortCut but may in some cases be more computational expensive.

Constructor Summary

Constructors

Constructor	Description
PathLengthOptimizer(long cPtr, boolean cMemoryOwn)
PathLengthOptimizer(PlannerConstraint constraint, MetricQCPtr metric)	Constructor Path optimization is based on a constraint for edges together with a distance metric to measure whether the path modifications decrease the length of the path.

Method Summary

Modifier and Type	Method	Description
void	delete()
static long	getCPtr(PathLengthOptimizer obj)
static java.lang.String	getPROP_LOOPCOUNT()	Property key for the maximal number of loops
static java.lang.String	getPROP_MAXTIME()	Property key for max time
static java.lang.String	getPROP_SUBDIVLENGTH()	Property key for length of segment in when subdividing
PropertyMap	getPropertyMap()	Returns the propertymap
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

PathLengthOptimizer

public PathLengthOptimizer(long cPtr,
                           boolean cMemoryOwn)

PathLengthOptimizer

public PathLengthOptimizer(PlannerConstraint constraint,
                           MetricQCPtr metric)

Constructor

Path optimization is based on a constraint for edges together with a
distance metric to measure whether the path modifications decrease
the length of the path.

Parameters:

constraint - [in] Verification of edges and configurations.

metric - [in] Distance metric for edge lengths

Method Detail

getCPtr

public static long getCPtr(PathLengthOptimizer obj)

delete

public void delete()

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 static java.lang.String getPROP_LOOPCOUNT()

Property key for the maximal number of loops

getPROP_MAXTIME

public static java.lang.String getPROP_MAXTIME()

Property key for max time

getPROP_SUBDIVLENGTH

public static java.lang.String getPROP_SUBDIVLENGTH()

Property key for length of segment in when subdividing