Resampling methods for particle filtering: plotParticlesUnweight( x, w ) - File Exchange

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Highlights from
Resampling methods for particle filtering

ESS( w )
Gauss( x )
countPathHypotheses(x)
covParticlesXY( x,y,w )
h=error_ellipse(varargin) ERROR_ELLIPSE - plot an error ellipse, or ellipsoid, defining confidence region
motionModel( X, action )
observationLikelihood( x, obs...
particleFilter( x,w, action, ... A simple SIS with resampling filter
plotParticles( x, w ) Dibuja un conjunto de particulas de "poses" del robot
plotParticlesFromFile( f ) Fondo negro:
plotParticlesUnweight( x, w ) Dibuja un conjunto de particulas de "poses" del robot
resample( w )
resampleMultinomial( w )
resampleResidual( w ) "Repetition counts" (plus the random part, later on):
resampleStratified( w )
resampleSystematic( w )
runExample(INTERACTIVE,RESAMP... The main script for running the Particle Filter example
runAnalysis.m
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from Resampling methods for particle filtering by Jose-Luis Blanco
Implementation of four resampling methods (Multinomial, Residual, Stratified, and Systematic)

plotParticlesUnweight( x, w )

function [ ] = plotParticlesUnweight( x, w )
% Dibuja un conjunto de particulas de "poses" del robot
%
% function [  ] = plotParticles( x, w )
%

plot(x(:,1),x(:,2),'.');


s = sprintf('mean=(%.02f,%.02f,%.1fdeg), std=(%.02f,%.02f,%.1fdeg)',mean(x(:,1)),mean(x(:,2)),mean(x(:,3))*180/pi,std(x(:,1)),std(x(:,2)),std(x(:,3))*180/pi);
title(s);

Highlights from Resampling methods for particle filtering

Highlights from
Resampling methods for particle filtering