forked from marynelv/IVCalibrationToolbox
-
Notifications
You must be signed in to change notification settings - Fork 0
/
synthesizeDataLookAtLandmarks.m
206 lines (153 loc) · 6.26 KB
/
synthesizeDataLookAtLandmarks.m
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
% IMU Simulation with camera directed towards mean landmark
%
% Coordinate frames:
% w: world frame
% i: IMU frame
% c: camera (right-down-forward) frame
%
% Variables:
% R: rotation 3-by-3
% T: transform 4-by-4
% q: quaternion 4-by-1
% a: acceleration 3-by-1
% v: velocity 3-by-1
% p: position 3-by-1
%% Clear the workspace
clear
close all
clc
%rng(1); % repeatable simulation results
%% Setup parameters
plotFlag = 1; % want a plot?
timeStep = 0.05; % delta T
t = 0:timeStep:5; % simulation run time and time step
a_w_c = repmat([-0.3 0.8 -0.1]', 1, length(t)); % constant linear acceleration for the camera
p0_w_c = [0 0 0]'; % initial camera position in the world
v0_w_c = [0.3 0.8 -0.1]*timeStep'; % initial camera velocity
q_i_c = [ 0.7071 0 0 0.7071 ]'; % rotation from IMU to camera
% p_i_c = [ 10 0 0]'; % translation from IMU to camera
%q_i_c = [ 1 0 0 0 ]'; % rotation from IMU to camera
p_i_c = [ 10 0 0]'; % translation from IMU to camera
numPoints = 100; % number of landmarks
pts_min = -5;
pts_max = 5;
pts_center = [10 10 0]'; % mean landmark
std_pixel_noise = 0.1;
std_v_w = 0.1;
gravity = [0 0 9.81]'; % gravity
image_width = 640; % image width
image_height = 480; % image height
f = 0.7; % focal length
%% Derived parameters
nSteps = length(t);
camera_x = repmat([1 0 0]',1,nSteps);
camera_y = repmat([0 -1 0]',1,nSteps);
camera_z = repmat([0 0 -1]',1,nSteps);
% camera stuff
pts_proj = zeros(2,numPoints); % landmarks projected into the image plane
px = image_width/2; py = image_height/2; % principal point
K = [f*image_width 0 px; 0 f*image_height py; 0 0 1]; % intrinsic parameters
%% Generate landmarks
pts_w = bsxfun(@plus, pts_min+(pts_max-pts_min).*rand(3,numPoints), pts_center);
%% Generate camera path first and find its orientation
q_w_c = zeros(4,nSteps);
v_w_c = zeros(3,nSteps);
%p_w_c=generatePosBspline(pts_w,nSteps);
p_w_c = zeros(3,nSteps);
v_w_c(:,1) = v0_w_c;
p_w_c(:,1) = p0_w_c;
q_w_c(:,1) = cameraOrientation(p_w_c(:,1), v_w_c(:,1), pts_center);
for i = 2:nSteps
dt = t(i) - t(i-1);
v_w_c(:,i) = v_w_c(:,i-1) + a_w_c(:,i-1)*dt;
p_w_c(:,i) = p_w_c(:,i-1) + v_w_c(:,i-1)*dt + 0.5*a_w_c(:,i-1)*dt^2;
q_w_c(:,i) = cameraOrientation(p_w_c(:,i), v_w_c(:,i), pts_center);
end
q_w_c(:,end)=q_w_c(:,end-1);
%% Position and orientation of IMU in the world frame
q_w_i=zeros(4,nSteps);
p_w_i=zeros(3,nSteps);
for i=1:nSteps
q_w_i(:,i)=rotation2quaternion(quaternion2rotation(q_w_c(:,i))/(quaternion2rotation(q_i_c)));
p_w_i(:,i)=p_w_c(:,i)+(quaternion2rotation(q_w_c(:,i))/(quaternion2rotation(q_i_c)))*(-p_i_c);
end
v_w_i=bsxfun(@rdivide,diff(p_w_i,1,2),diff(t,1));
a_w_i=bsxfun(@rdivide,diff(v_w_i,1,2),diff(t(1:end-1),1));
v_w_i=[v_w_i,v_w_i(:,end)];
a_w_i=[a_w_i,a_w_i(:,end-1:end)];
%[v_w_i,a_w_i,omega_w_i,alpha_w_i]=getVelocityAcceleration(p_w_i,q_w_i,t);
%% Position camera axis throughout simulation
for i = 1:nSteps
camera_x(:,i) = p_w_c(:,i) + quaternionRotate(q_w_c(:,i)', camera_x(:,i))*5;
camera_y(:,i) = p_w_c(:,i) + quaternionRotate(q_w_c(:,i)', camera_y(:,i))*5;
camera_z(:,i) = p_w_c(:,i) + quaternionRotate(q_w_c(:,i)', camera_z(:,i))*5;
end
%% Projected points
observed_pts_c = NaN * ones(2*numPoints, length(t));
for i = 1:length(t)
% [px py]' = K*R[ I | -C ] * [x y z 1]'
for p = 1:numPoints
% xyz = K*quaternion2rotation(q_w_c(:,i))'*(pts_w(:,p) - p_w_c(:,i));
xyz = K*quaternion2rotation(q_w_c(:,i))'*[eye(3) -p_w_c(:,i)]*[pts_w(:,p); 1];
pts_proj(1,p) = xyz(1)/xyz(3);
pts_proj(2,p) = xyz(2)/xyz(3);
end
observed_pts_c(:,i)=pts_proj(:);
end
%% Rename stuff like before
a_w = a_w_i;
v_w = v_w_i;
p_w = p_w_i;
std_dev_noise_accel = 0;
std_dev_bias_accel = 0;
std_dev_noise_gyro = 0;
bias_accel = zeros(size(a_w_i));
noise_accel = std_dev_noise_accel*randn(size(a_w_i));
accel_i_measured = a_w_i + bias_accel + noise_accel;
w = repmat([0 0 0]', 1, length(t));
bias_gyro = zeros(size(w));
noise_gyro = std_dev_noise_gyro*randn(size(w));
gyro_i_measured = w + bias_gyro + noise_gyro;
imuData = zeros(length(t), 31);
imuData(:,3) = t;
imuData(:,17:19) = gyro_i_measured';
imuData(:,29:31) = accel_i_measured';
camData = zeros(length(t), 3);
camData(:,3) = t;
%% Create noisy measurements
noisy_v_w = v_w + std_v_w*randn(size(v_w));
noisy_observed_pts_c = observed_pts_c + std_pixel_noise*randn(size(observed_pts_c));
%% Plot
if plotFlag
for i = 1:length(t) - 1
figure(1);
grid on;
% plot points
subplot(1,2,1);
scatter3(pts_w(1, :), pts_w(2, :), pts_w(3, :), 'r', '.');
hold on;
scatter3(pts_center(1), pts_center(2), pts_center(3), 'b', '.');
% plot3([p_w_c(1,i) pts_center(1)], [p_w_c(2,i) pts_center(2)], [p_w_c(3,i) pts_center(3)],'m-');
% plot camera path
plot3(p_w_c(1,:), p_w_c(2,:), p_w_c(3,:), 'k-');
% draw camera axis
plot3([p_w_c(1,i) camera_x(1,i)], [p_w_c(2,i) camera_x(2,i)], [p_w_c(3,i) camera_x(3,i)], 'r');
plot3([p_w_c(1,i) camera_y(1,i)], [p_w_c(2,i) camera_y(2,i)], [p_w_c(3,i) camera_y(3,i)], 'g');
plot3([p_w_c(1,i) camera_z(1,i)], [p_w_c(2,i) camera_z(2,i)], [p_w_c(3,i) camera_z(3,i)], 'b');
% draw imu
plot3([p_w_c(1,i) p_w_i(1,i)], [p_w_c(2,i) p_w_i(2,i)], [p_w_c(3,i) p_w_i(3,i)], 'c-');
axis equal; axis vis3d;
axis([-10 30 -5 45 -30 30]);
xlabel('x'); ylabel('y'); zlabel('z');
title(sprintf('frame %d/%d', i, length(t)-1));
view([-41 36]);
hold off;
subplot(1,2,2);
scatter(observed_pts_c(1:2:end,i), observed_pts_c(2:2:end,i), 'r');
axis equal;
axis([0 image_width 0 image_height]);
xlabel('x'); ylabel('-y');
title('Camera image');
pause(0.1);
end
end