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ComplexEdge_Vision_Example_Small.m
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ComplexEdge_Vision_Example_Small.m
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clc
clear
addpath('./g2o_files/');
addpath('./auxilliary/')
addpath('./Math/');
addpath('./Factor/');
pose0=[eye(3) zeros(3,1)];
pose1=[expm(skew([ 0.1 ;-0.05; 0.2 ])) [ 2; -2 ;-1] ];
pose2=[expm(skew([ -0.15 ; 0.05; -0.2 ])) [ -1.5; 2.3 ;-1.2] ];
pose3=[expm(skew([ 0.4 ; -0.1; 0.35 ])) [ -3; -2.7 ;-2] ];
f=cell(1,10);
f{1} = [ 1; 2 ;9 ];
f{2} = [ -1; 2 ;7];
f{3} = [ -2; 1 ; 11 ];
f{4} = [ -1.5; 2.4 ; 7.6 ];
f{5}= [ 3; 2 ; 9.4 ];
f{6}= [ -4; 4 ; 14 ];
f{7}= [ 4; -6 ; 10 ];
f{8}= [ 5; -2 ; 9.5 ];
f{9}= [ 0; 0 ; 4 ];
f{10}= [ 0.2; 0.5 ; 5 ];
fprintf('Ground Truth of landmarks\n')
[ Graph ] = InitializeGraph;
Graph.Fixed.IDname.pose0 = 1;
%Graph.Fixed.IDname.pose1 = 1;
k=0;
for i=1:10
fea = f{i};
[ UV_i_0 ] = GenerateUV_randn( pose0, f{i} );
R = pose0(1:3,1:3); p = pose0(1:3,4); d = norm(R'*( fea - p ));
Measurement_i_0.value = UV_i_0;
NodeArray=cell(2,2);
NodeArray{1,1}='Pose3';NodeArray{1,2}='pose0';
NodeArray{2,1}='Landmark3';NodeArray{2,2}=['landmark' num2str(i)];
if k
Measurement_i_0.inf = eye(2); %eye(2)/(d^2)*525^2;
[ Graph ] = AddComplexEdge( Graph, 'LinearVision_Factor', NodeArray, Measurement_i_0 );
else
Measurement_i_0.inf = eye(2);
[ Graph ] = AddComplexEdge( Graph, 'Vision_Factor', NodeArray, Measurement_i_0 );
end
[ UV_i_1 ] = GenerateUV_randn( pose1, f{i} );
R = pose1(1:3,1:3); p = pose1(1:3,4); d = norm(R'*( fea - p ));
Measurement_i_1.value = UV_i_1;
Measurement_i_1.inf = eye(2)/(d^2)*525^2;
NodeArray{1,2}='pose1';
if k
Measurement_i_1.inf = eye(2); %eye(2)/(d^2)*525^2;
[ Graph ] = AddComplexEdge( Graph, 'LinearVision_Factor', NodeArray, Measurement_i_1 );
else
Measurement_i_1.inf = eye(2);
[ Graph ] = AddComplexEdge( Graph, 'Vision_Factor', NodeArray, Measurement_i_1 );
end
[ UV_i_2 ] = GenerateUV_randn( pose2, f{i} );
R = pose2(1:3,1:3); p = pose2(1:3,4); d = norm(R'*( fea - p ));
Measurement_i_2.value = UV_i_2;
Measurement_i_2.inf = eye(2)/(d^2);
NodeArray{1,2}='pose2';
if k
Measurement_i_2.inf = eye(2); %eye(2)/(d^2)*525^2;
[ Graph ] = AddComplexEdge( Graph, 'LinearVision_Factor', NodeArray, Measurement_i_2 );
else
Measurement_i_2.inf = eye(2);
[ Graph ] = AddComplexEdge( Graph, 'Vision_Factor', NodeArray, Measurement_i_2 );
end
[ UV_i_3 ] = GenerateUV_randn( pose3, f{i} );
R = pose3(1:3,1:3); p = pose3(1:3,4); d = norm(R'*( fea - p ));
Measurement_i_3.value = UV_i_3;
Measurement_i_3.inf = eye(2)/(d^2);
NodeArray{1,2}='pose3';
if k
Measurement_i_3.inf = eye(2); % eye(2)/(d^2)*525^2;
[ Graph ] = AddComplexEdge( Graph, 'LinearVision_Factor', NodeArray, Measurement_i_3 );
else
Measurement_i_3.inf = eye(2);
[ Graph ] = AddComplexEdge( Graph, 'Vision_Factor', NodeArray, Measurement_i_3 );
end
end
%%% Set initial guess via ground truth+noise
Graph.Nodes.Pose3.Values.pose0=pose0;
noise1 = [ expm(skew(randn(3,1)*0)) randn(3,1)*0];
Graph.Nodes.Pose3.Values.pose1=se3_group(pose1, noise1 ) ;
noise2 = [ expm(skew(randn(3,1)*0.1)) randn(3,1)*0.2];
Graph.Nodes.Pose3.Values.pose2=se3_group(pose2, noise2 ) ;
noise3 = [ expm(skew(randn(3,1)*0.1)) randn(3,1)*0.2];
Graph.Nodes.Pose3.Values.pose3=se3_group(pose3, noise3 ) ;
Y=cell(10,1);
for i=1:10
G_i=f{i};
Graph.Nodes.Landmark3.Values.(['landmark' num2str(i)])=f{i}+1*randn(3,1);
X_i=Graph.Nodes.Landmark3.Values.(['landmark' num2str(i)]);
Y{i}=X_i;
end
%Graph.Nodes.Landmark3.Values.landmark1=[1.02;2.1;9.1];
%Y{1} = [1;1;1];
%%% Set initial guess
%[ Graph ] = PerformGO( Graph );
tic
[ Graph ] = PerformGO_DL( Graph );
toc
%[ Graph ] = PerformGO( Graph );
for i=1:10
G_i=f{i};
X_i=Graph.Nodes.Landmark3.Values.(['landmark' num2str(i)]);
Y_i=Y{i};
fprintf('%d, %f, %f, %f \n', i, G_i(1),X_i(1),Y_i(1) )
fprintf('%d, %f, %f, %f \n', i, G_i(2),X_i(2),Y_i(2) )
fprintf('%d, %f, %f, %f \n', i, G_i(3),X_i(3),Y_i(3) )
end