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particle_filter5.m
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particle_filter5.m
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clear; %close all;clc;
%Load projective transform matrix
load('tform.mat');
%load('f00123.png.mat');
%Image width
img_width = 360;
%SkySize
sky = 0.6*404;
%Image directory
img_directory = 'our_data/';
%Create a particle filter object
pf = robotics.ParticleFilter;
pfC = robotics.ParticleFilter;
%Choose resmapling policy
policy = robotics.ResamplingPolicy;
%policy.TriggerMethod = 'interval';
%policy.SamplingInterval = 2;
pf.ResamplingPolicy = policy;
%pfC.ResamplingPolicy = policy;
%pfC.StateEstimationMethod = 'maxweight';
%Choose the likelihood function for particle filter
pf.MeasurementLikelihoodFcn = @measurementLikelihoodFcn3;
pfC.MeasurementLikelihoodFcn = @paramLikelihoodFcn;
%Define the state transition function
pf.StateTransitionFcn = @stateTransitionFcn3;
pfC.StateTransitionFcn = @paramStateTransitionFcn;
%% Initilize the particle filter
mean = [img_width/4,img_width*(3/4)];
covariance = img_width/4*eye(2);
initialize(pf,1000,mean,covariance);
%Initilize second particle filter-pfC
%[0.0007 -0.2586 422.3815];
initilParam = [0 0 422]';
initialParamCov = zeros(3);
initialParamCov(1,1) = 0.001;
initialParamCov(2,2) = 0.2;
initialParamCov(3,3) = 10;
initialize(pfC,1000,initilParam,initialParamCov);
%Define counter for image writing
ii= 1;
%Define state Estimate
stateEst =zeros(1,2);
stateEstC = zeros(1,3);
%Initial and last time frame
iT = 835;
T = 7000;
%Particle filter iteration
for i=iT:T %i=time stamp
tic,
%% Prediction - (drift and diffusion)
%figure();plot(pf_Right.Particles);hold on;
[statePredicted,stateCov] = predict(pf,pf.Particles,stateEst);
%plot(pf_Right.Particles,'r');
%% Measurement from current image
%For now measuremnet is horizontal histogram
%Read the image
img_name = strcat(img_directory,num2str(i),'.jpg');
img= imread(img_name);
%Find a histogram for lower image
[lower_map,edge_map_small,img_crop ,img_tf] = cues2( img,tform1);
lower_map_right = lower_map(:,size(lower_map,2)/2:end);
lower_map_left = lower_map(:,1:size(lower_map,2)/2);
%measurement is histogram
measurement_right = sum(lower_map_right);
if norm(measurement_right) >0
measurement_right = measurement_right/norm(measurement_right)+ 2/length(measurement_right);
else
measurement_right = (5/length(measurement_right))*ones(1,size(lower_map_right,2));
end
measurement_left = sum(lower_map_left);
if norm(measurement_left) >0
measurement_left = measurement_left/norm(measurement_left)+ 2/length(measurement_left);
else
measurement_left = (5/length(measurement_left))*ones(1,size(lower_map_left,2));
end
%% Prediction - pfC
[statePredictedC,stateCovC] = predict(pfC,pfC.Particles,stateEstC);
%% Correct weights by using measurement
[stateCorrected,stateCov] = correct(pf,measurement_right,measurement_left);
%% Estimate the state according to selected estimation method (default:mean)
stateEst = getStateEstimate(pf);
%% --------------------------------------------------------------------------------
%% Upper part - could be curved
% Measurement from RANSAC
[pr,pl,estDiff] = curved_road2(edge_map_small,stateEst(1),stateEst(2));
%% Correct weights by using measurement
[stateCorrectedC,stateCovC] = correct(pfC,stateEst,pr,pl);
%% Estimate the state according to selected estimation method (default:mean)
stateEstC = getStateEstimate(pfC);
%% Consistency Check
% if ii==1;
% previousPoly = pr;
% end
% [consistent, previousPoly] = consistency_check( pr,pl, previousPoly,stateEst );
%
% pr = consistent*pr + (1-consistent)*previousPoly;
%% Generate points on lines
yr = (-400:10:250)';
xr = polyval(stateEstC,yr);
yr = 2*yr;
xr = 2*xr;
%xr = xr - (xr(find(yr == 160))-(stateEst(2)+560));
yl = yr;
xl = xr - 2*estDiff;
%Find the point in the real image
[uR,vR] = tforminv(tform1,xr-200,yr-500);
[uL,vL] = tforminv(tform1,xl-200,yl-500);
vR = vR+242;
vL = vL+242;
uvR = [uR,vR];
uvL = [uL,vL];
%% Visulize
%Find the point in the real image
[uR,vR] = tforminv(tform1,stateEst(2)+360,160);
[uL,vL] = tforminv(tform1,stateEst(1),160);
%Extra 2 points for drawing
[uRE,vRE] = tforminv(tform1,stateEst(2)+360,-10);
[uLE,vLE] = tforminv(tform1,stateEst(1),-10);
%img_mark = insertShape(img,'FilledCircle',[uL,size(img,1)-10,5],'LineWidth',3, 'Color','blue');
%img_mark = insertShape(img_mark,'FilledCircle',[uR,size(img,1)-10,5],'LineWidth',3, 'Color','red');
%Draw polygon on the input image
% polygon_points = [uL,vL+sky,uLE,vLE+sky,uRE,vRE+sky,uR,vR+sky];
% img_mark = insertShape(img,'FilledPolygon',polygon_points,'LineWidth',1, 'Color','green');
%
% %polygon_points = [[uL,vL+sky;uLE,vLE+sky];flipud(uvL); uvR;[uRE,vRE+sky;uR,vR+sky]];
% polygon_points = [uvL; flipud(uvR)];
% polygon_points = polygon_points';
% polygon_points = polygon_points(:);
% polygon_points = polygon_points';
% img_mark = insertShape(img_mark,'FilledPolygon',polygon_points,'LineWidth',1, 'Color','red');
%img_mark = insertShape(img_tf,'FilledCircle',[stateEst(1)+200,size(img_tf,1)-20,5],'LineWidth',3,'Color','red');
%img_mark = insertShape(img_mark,'FilledCircle',[[uvL;uvR],2*ones(size(uvL,1)+size(uvR,1),1)],'LineWidth',1);
%imshow(img_mark);
% %Image Writing
% filename = [sprintf('%03d',ii) '.jpg'];
% fullname = fullfile('curved2/',filename);
% imwrite(img_mark,fullname) % Write out to a JPEG file (img1.jpg, img2.jpg, etc.)
% ii = ii+1;
toc
end