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2D/3D point and pose PDFs

Detailed Description

Collaboration diagram for 2D/3D point and pose PDFs:

Classes

class  mrpt::poses::CPoint2DPDF
 Declares a class that represents a Probability Distribution function (PDF) of a 2D point (x,y). More...
 
class  mrpt::poses::CPoint2DPDFGaussian
 A gaussian distribution for 2D points. More...
 
class  mrpt::poses::CPointPDF
 Declares a class that represents a Probability Distribution function (PDF) of a 3D point (x,y,z). More...
 
class  mrpt::poses::CPointPDFGaussian
 A gaussian distribution for 3D points. More...
 
class  mrpt::poses::TSimple3DPoint
 Data within each particle. More...
 
class  mrpt::poses::CPointPDFParticles
 A probability distribution of a 2D/3D point, represented as a set of random samples (particles). More...
 
class  mrpt::poses::CPointPDFSOG
 Declares a class that represents a Probability Density function (PDF) of a 3D point $ p(\mathbf{x}) = [x ~ y ~ z ]^t $. More...
 
class  mrpt::poses::CPose2DGridTemplate< T >
 This is a template class for storing a 3D (2D+heading) grid containing any kind of data. More...
 
class  mrpt::poses::CPose3DPDF
 Declares a class that represents a Probability Density Function (PDF) of a 3D pose (6D actually). More...
 
class  mrpt::poses::CPose3DPDFGaussian
 Declares a class that represents a Probability Density function (PDF) of a 3D pose $ p(\mathbf{x}) = [x ~ y ~ z ~ yaw ~ pitch ~ roll]^t $. More...
 
class  mrpt::poses::CPose3DPDFGaussianInf
 Declares a class that represents a Probability Density function (PDF) of a 3D pose $ p(\mathbf{x}) = [x ~ y ~ z ~ yaw ~ pitch ~ roll]^t $ as a Gaussian described by its mean and its inverse covariance matrix. More...
 
class  mrpt::poses::CPose3DPDFParticles
 Declares a class that represents a Probability Density function (PDF) of a 3D pose. More...
 
class  mrpt::poses::CPose3DPDFSOG
 Declares a class that represents a Probability Density function (PDF) of a 3D(6D) pose $ p(\mathbf{x}) = [x ~ y ~ z ~ yaw ~ pitch ~ roll]^t $. More...
 
class  mrpt::poses::CPose3DQuatPDF
 Declares a class that represents a Probability Density Function (PDF) of a 3D pose (6D actually), by means of a 7-vector with a translation [x y z] and a quaternion [qr qx qy qz]. More...
 
class  mrpt::poses::CPose3DQuatPDFGaussian
 Declares a class that represents a Probability Density function (PDF) of a 3D pose using a quaternion $ p(\mathbf{x}) = [x ~ y ~ z ~ qr ~ qx ~ qy ~ qz]^\top $. More...
 
class  mrpt::poses::CPose3DQuatPDFGaussianInf
 Declares a class that represents a Probability Density function (PDF) of a 3D pose using a quaternion $ p(\mathbf{x}) = [x ~ y ~ z ~ qr ~ qx ~ qy ~ qz]^\top $. More...
 
class  mrpt::poses::CPosePDF
 Declares a class that represents a probability density function (pdf) of a 2D pose (x,y,phi). More...
 
class  mrpt::poses::CPosePDFGaussian
 Declares a class that represents a Probability Density function (PDF) of a 2D pose $ p(\mathbf{x}) = [x ~ y ~ \phi ]^t $. More...
 
class  mrpt::poses::CPosePDFGaussianInf
 A Probability Density function (PDF) of a 2D pose $ p(\mathbf{x}) = [x ~ y ~ \phi ]^t $ as a Gaussian with a mean and the inverse of the covariance. More...
 
class  mrpt::poses::CPosePDFGrid
 Declares a class that represents a Probability Distribution function (PDF) of a 2D pose (x,y,phi). More...
 
class  mrpt::poses::CPosePDFParticles
 Declares a class that represents a Probability Density Function (PDF) over a 2D pose (x,y,phi), using a set of weighted samples. More...
 
class  mrpt::poses::CPosePDFSOG
 Declares a class that represents a Probability Density function (PDF) of a 2D pose $ p(\mathbf{x}) = [x ~ y ~ \phi ]^t $. More...
 
class  mrpt::poses::CPoseRandomSampler
 An efficient generator of random samples drawn from a given 2D (CPosePDF) or 3D (CPose3DPDF) pose probability density function (pdf). More...
 
class  mrpt::poses::CRobot2DPoseEstimator
 A simple filter to estimate and extrapolate the robot 2D (x,y,phi) pose from asynchronous odometry and localization/SLAM data. More...
 

Namespaces

 mrpt::poses
 Classes for 2D/3D geometry representation, both of single values and probability density distributions (PDFs) in many forms.
 



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