An abstract class for the concept of using deterministic sampling sequences to decrease the dispersion of the samples. More...
#include <ompl/base/samplers/DeterministicStateSampler.h>
Public Types  
enum  DeterministicSamplerType { HALTON } 
Public Member Functions  
DeterministicStateSampler (const StateSpace *space, DeterministicSamplerType type=DeterministicSamplerType::HALTON)  
Constructor, which creates the sequence internally based on the specified sequence type. Uses the default constructor for the sequence.  
DeterministicStateSampler (const StateSpace *space, std::shared_ptr< DeterministicSequence > sequence_ptr)  
Constructor that takes a pointer to a DeterministicSequence and uses that object instead of its own. This can be used to apply non default options to the deterministic sequence.  
virtual void  sampleUniform (State *state) 
Sample a state.  
virtual void  sampleUniformNear (State *, const State *, double) 
Sample a state near another, within a neighborhood controlled by a distance parameter. More...  
virtual void  sampleGaussian (State *, const State *, double) 
Sample a state using a Gaussian distribution with given mean and standard deviation (stdDev). More...  
Public Member Functions inherited from ompl::base::StateSampler  
StateSampler (const StateSampler &)=delete  
StateSampler &  operator= (const StateSampler &)=delete 
StateSampler (const StateSpace *space)  
Constructor.  
Protected Attributes  
std::shared_ptr< DeterministicSequence >  sequence_ptr_ 
Protected Attributes inherited from ompl::base::StateSampler  
const StateSpace *  space_ 
The state space this sampler samples.  
RNG  rng_ 
An instance of a random number generator.  
Detailed Description
An abstract class for the concept of using deterministic sampling sequences to decrease the dispersion of the samples.
 Short description
 DeterministicStateSampler Implementation of a deterministic state sampler. The implementation allows to load and draw samples from a precomputed sequence or from the Halton Sequence,
 External documentation
 Dispertio: Optimal Sampling For Safe Deterministic Motion Planning L Palmieri, L Bruns, M Meurer, KO Arras  IEEE Robotics and Automation Letters, 2019 DOI: 10.1109/LRA.2019.2958525
[PDF]
Definition at line 64 of file DeterministicStateSampler.h.
Member Function Documentation
◆ sampleGaussian()

inlinevirtual 
Sample a state using a Gaussian distribution with given mean and standard deviation (stdDev).
As with sampleUniform, the implementation of sampleGaussian is specific to the derived class and few assumptions can be made about the distance between state
and mean
.
Implements ompl::base::StateSampler.
Reimplemented in ompl::base::SE2DeterministicStateSampler, ompl::base::RealVectorDeterministicStateSampler, and ompl::base::SO2DeterministicStateSampler.
Definition at line 93 of file DeterministicStateSampler.h.
◆ sampleUniformNear()

inlinevirtual 
Sample a state near another, within a neighborhood controlled by a distance parameter.
Typically, StateSamplerderived classes will return in state
a state that is uniformly distributed within a ball with radius distance
defined by the distance function from the corresponding state space. However, this is not guaranteed. For example, the default state sampler for the RealVectorStateSpace returns samples uniformly distributed using L_inf distance, while the default distance function is L_2 distance.
Implements ompl::base::StateSampler.
Reimplemented in ompl::base::SE2DeterministicStateSampler, ompl::base::RealVectorDeterministicStateSampler, and ompl::base::SO2DeterministicStateSampler.
Definition at line 89 of file DeterministicStateSampler.h.
The documentation for this class was generated from the following files:
 ompl/base/samplers/DeterministicStateSampler.h
 ompl/base/samplers/src/DeterministicStateSampler.cpp