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main.cpp
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#include <stdlib.h>
#include <stdio.h>
#include <cv.h>
#include <cvaux.h>
#include <highgui.h>
#include <sys/time.h>
#include <math.h>
#include "common.h"
#include "kalmanClass.h"
#include "capture.h"
#include "featureDetector.h"
#include "displayClass.h"
#include "dataAssocClass.h"
#include "curveFittingClass.h"
#include "pointFeaturesClass.h"
#include <iostream>
#include <fstream>
//#define USE_POINTS //Whether or not point features should be used
#ifdef QUAD
#define LEFT_IMAGE_LAG 0
#else
#ifdef MEADOWBROOK
#define LEFT_IMAGE_LAG 0
#else
#ifdef CRYSTAL_LAKE
#define LEFT_IMAGE_LAG 2
#else
#define LEFT_IMAGE_LAG 2
#endif
#endif
#endif
#define ERROR_THRESHOLD 50000.0
//#define ERROR_THRESHOLD 23000.0
#define FRAME_INTERVAL 1
//#define FRAMES_TO_SKIP 3101
#define FRAMES_TO_SKIP 300
#define NUM_FRAMES_DA_RESET 2 //Number of frames without a valid curve measurement after which
//we reset the data association and start with new curves
#define CURVE_MIN_OBS 0.5 //Min amount of a curve that needs to be observed before it is introduced
using namespace std;
timeval t_start, t_stop;
timeval start, stop;
float elapsedTime;
CvPoint last_pts[2];
CvPoint current_pts[2];
unsigned int binom[50][50];
int main(void)
{
int cam_index[2];
cam_index[LEFT] = 1;
cam_index[RIGHT] = 2;
//Define classes
CaptureDevice *camera = new CaptureDevice[NUM_CAMERAS];
DisplayClass *display_GUI = new DisplayClass;
KalmanFilter *EKF = new KalmanFilter;
CurveFittingClass * curveFitter = new CurveFittingClass;
DataAssocClass * curveMatcher = new DataAssocClass[2];
FeatureDetector *features = new FeatureDetector[NUM_CAMERAS];
PointFeaturesClass *pointFeatures = new PointFeaturesClass;
//Define image data
IplImage * image[NUM_CAMERAS];
IplImage * image_raw[NUM_CAMERAS];
IplImage * last_image_raw[NUM_CAMERAS];
IplImage * seg[NUM_CAMERAS];
IplImage * image_color[NUM_CAMERAS];
IplImage * last_image_color[NUM_CAMERAS];
IplImage * last_image[NUM_CAMERAS];
IplImage * last_image_track[NUM_CAMERAS];
//Stereo rectification parameters
CvSize imageSize = cvSize(PIC_WIDTH,PIC_HEIGHT);
CvMat * mx[2], * my[2];
mx[0] = cvCreateMat( imageSize.height,
imageSize.width, CV_32F );
my[0] = cvCreateMat( imageSize.height,
imageSize.width, CV_32F );
mx[1] = cvCreateMat( imageSize.height,
imageSize.width, CV_32F );
my[1] = cvCreateMat( imageSize.height,
imageSize.width, CV_32F );
CvMat* disp = cvCreateMat( imageSize.height,
imageSize.width, CV_16S );
CvRect roi[2];
CvMat *M1 = cvCreateMat(3, 3, CV_64F);
CvMat *M2 = cvCreateMat(3, 3, CV_64F);
CvMat *D1 = cvCreateMat(1, 5, CV_64F);
CvMat *D2 = cvCreateMat(1, 5, CV_64F);
CvMat *R = cvCreateMat(3, 3, CV_64F);
CvMat *T = cvCreateMat(3, 1, CV_64F);
CvMat *R1 = cvCreateMat(3, 3, CV_64F);
CvMat *R2 = cvCreateMat(3, 3, CV_64F);
CvMat *P1 = cvCreateMat(3, 4, CV_64F);
CvMat *P2 = cvCreateMat(3, 4, CV_64F);
CvMat *Q = cvCreateMat(4, 4, CV_64F);
cvSetZero(M1);
cvSetZero(M2);
cvSetZero(D1);
cvSetZero(D2);
cvSetZero(R1);
cvSetZero(R2);
cvSetZero(P1);
cvSetZero(P2);
cvSetZero(R);
cvSetZero(T);
cvSetZero(Q);
M1->data.db[0] = FX0;
M1->data.db[2] = CX0;
M1->data.db[4] = FY0;
M1->data.db[5] = CY0;
M2->data.db[0] = FX1;
M2->data.db[2] = CX1;
M2->data.db[4] = FY1;
M2->data.db[5] = CY1;
R->data.db[0] = R11;
R->data.db[1] = R12;
R->data.db[2] = R13;
R->data.db[3] = R21;
R->data.db[4] = R22;
R->data.db[5] = R23;
R->data.db[6] = R31;
R->data.db[7] = R32;
R->data.db[8] = R33;
T->data.db[0] = -T1;
T->data.db[1] = -T2;
T->data.db[2] = -T3;
D1->data.db[0] = D01;
D1->data.db[1] = D02;
D1->data.db[2] = D03;
D1->data.db[3] = D04;
D1->data.db[4] = D05;
D2->data.db[0] = D11;
D2->data.db[1] = D12;
D2->data.db[2] = D13;
D2->data.db[3] = D14;
D2->data.db[4] = D15;
cvStereoRectify( M1, M2, D1, D2, imageSize,
R, T,
R1, R2, P1, P2, Q,
CV_CALIB_ZERO_DISPARITY,
1, imageSize, &(roi[0]), &(roi[1]));
//Precompute maps for cvRemap() - part of stereo rectification
cvInitUndistortRectifyMap(M1,D1,R1,P1,mx[0],my[0]);
cvInitUndistortRectifyMap(M2,D2,R2,P2,mx[1],my[1]);
//Initialise the capture for both cameras (videos)
for (int i = 0; i < NUM_CAMERAS; ++i)
{
camera[i].init_capture(cam_index[i]); //+1 is so we dont use the laptop webcam
}
//Initialise binomial lookuptable
for (int n = 0; n < 50; n++)
{
for (int k = 0; k < 50; k++)
{
if (k == 0)
binom[n][k] = 1;
else if (n == 0)
binom[n][k] = 0;
else
binom[n][k] = binom[n-1][k]+binom[n-1][k-1];
}
}
//Initialise image data structs
CvSize frame_size = cvSize(PIC_WIDTH,PIC_HEIGHT);
last_image[0] = cvCreateImage( frame_size, IPL_DEPTH_8U, 1 );
last_image[1] = cvCreateImage( frame_size, IPL_DEPTH_8U, 1 );
last_image_raw[0] = cvCreateImage( frame_size, IPL_DEPTH_8U, 3 );
last_image_raw[1] = cvCreateImage( frame_size, IPL_DEPTH_8U, 3 );
last_image_track[0] = cvCreateImage( frame_size, IPL_DEPTH_8U, 1 );
last_image_track[1] = cvCreateImage( frame_size, IPL_DEPTH_8U, 1 );
image_color[0] = cvCreateImage( frame_size, IPL_DEPTH_8U, 3 );
image_color[1] = cvCreateImage( frame_size, IPL_DEPTH_8U, 3 );
image[0] = cvCreateImage( frame_size, IPL_DEPTH_8U, 1 );
image[1] = cvCreateImage( frame_size, IPL_DEPTH_8U, 1 );
last_image_color[0] = cvCreateImage( frame_size, IPL_DEPTH_8U, 3 );
last_image_color[1] = cvCreateImage( frame_size, IPL_DEPTH_8U, 3 );
//Initialise windows
cvNamedWindow("Left");
cvNamedWindow("Right");
cvMoveWindow("Left",0,0);
cvMoveWindow("Right",320,0);
//Get frames from camera
for (int n = 0; n < FRAMES_TO_SKIP; n++)
{
for (int i = 0; i < NUM_CAMERAS; ++i)
{
image_raw[i] = camera[i].get_frame();
}
}
//Get extra from either left or right camera based on what we think the lag is
//(Need frames to be synchronised)
for (int i = 0; i < LEFT_IMAGE_LAG; ++i)
{
image_raw[0] = camera[0].get_frame();
}
if (LEFT_IMAGE_LAG < 0)
{
for (int i = 0; i < -LEFT_IMAGE_LAG; ++i)
{
image_raw[1] = camera[1].get_frame();
}
}
//Stereo rectify initial image
cvRemap(image_raw[0], image_color[0], mx[0], my[0]);
cvRemap(image_raw[1], image_color[1], mx[1], my[1]);
cvCopy(image_raw[0],image_color[0],NULL);
cvCopy(image_raw[1],image_color[1],NULL);
//Init RNG
CvRandState randstate;
cvRandInit(&randstate,0.1,0.0,0xffffffff,CV_RAND_NORMAL);
//Mats to store measurement vectors of different sizes
CvMat *z8 = cvCreateMat(8,1,CV_64FC1);
CvMat *z16 = cvCreateMat(19,1,CV_64FC1);
CvMat *z = cvCreateMat(35,1,CV_64FC1);
CvMat *z1 = cvCreateMat(4,1,CV_64FC1);
CvMat *z2 = cvCreateMat(4,1,CV_64FC1);
CvMat *z3 = cvCreateMat(4,1,CV_64FC1);
CvMat *z4 = cvCreateMat(4,1,CV_64FC1);
CvMat *z_left = cvCreateMat(16,1,CV_64FC1);
CvMat *z_right = cvCreateMat(16,1,CV_64FC1);
std::vector<double> state_limits; //Stores the 'limits' of each curves (ie. what we've observed of it; full observation is 0 to 1)
//Curve control point transformation matrices
CvMat * A1 = cvCreateMat(4,4,CV_64FC1);
CvMat * A2 = cvCreateMat(4,4,CV_64FC1);
CvMat * A1l = cvCreateMat(4,4,CV_64FC1);
CvMat * A2l = cvCreateMat(4,4,CV_64FC1);
CvMat * B1l = cvCreateMat(4,4,CV_64FC1);
CvMat * B2l = cvCreateMat(4,4,CV_64FC1);
CvMat * A1r = cvCreateMat(4,4,CV_64FC1);
CvMat * A2r = cvCreateMat(4,4,CV_64FC1);
CvMat * B1r = cvCreateMat(4,4,CV_64FC1);
CvMat * B2r = cvCreateMat(4,4,CV_64FC1);
CvMat * I4 = cvCreateMat(4,4,CV_64FC1);
cvSetZero(I4);
I4->data.db[0] = 1.0;
I4->data.db[5] = 1.0;
I4->data.db[10] = 1.0;
I4->data.db[15] = 1.0;
int counter = 0;
//Initialise guess params (just in case the first curve fit fails!)
double params[19];
for (int i = 0; i < 16; i++)
params[i] = 0.0;
params[16] = 0.0;
params[17] = -0.2;
params[18] = -2.0;
double last_params[19];
for (int i = 0; i < 16; i++)
params[i] = 0.0;
params[16] = 0.0;
params[17] = -0.2;
params[18] = -2.0;
//Flags to determine what to do with the left and right curves (state machine)
char left_assoc_flag = ADD_FIRST_STATES;
char right_assoc_flag = ADD_FIRST_STATES;
bool partial_curve_observed[2] = {false, false};
bool first_time = true;
std::vector<int> left_curve_nums;
std::vector<int> right_curve_nums;
std::vector<int> curves_updated_last;
curves_updated_last.push_back(0);
curves_updated_last.push_back(1);
std::vector<int> curves_to_update;
int num_map_curves = 0;
double t_split[6];
double last_t_split[6];
bool edges_detected = true;
bool reset_data_assoc = true;
bool valid_measurement = true;
bool valid_last_measurement = true;
int frames_since_good_measurement = 0;
bool use_points = false; //Flag we set on the fly to decide if we need points or not
double t_split_default[] = {0.0,0.0,0.0};
double * t_splitL = &t_split_default[0];
double * t_splitR = &t_split_default[0];
//MAIN LOOP OVER VIDEO FRAMES
int count = 0;
while(1)
{
count++;
//cout << valid_measurement << " " << frames_since_good_measurement << endl;
if(valid_measurement)
{
frames_since_good_measurement = 1;
use_points = false;
}
else
frames_since_good_measurement++;
if (edges_detected = false || first_time)
{
reset_data_assoc = true;
valid_measurement = true;
}
else if (frames_since_good_measurement >= NUM_FRAMES_DA_RESET)
{
reset_data_assoc = true;
//use_points = true;
use_points = false;
}
else
reset_data_assoc = false;
valid_last_measurement = valid_measurement;
cvCopy(image_raw[0], last_image_raw[0], NULL);
cvCopy(image_raw[1], last_image_raw[1], NULL);
cvCvtColor(last_image_raw[0],last_image[0],CV_RGB2GRAY);
cvCvtColor(last_image_raw[1],last_image[1],CV_RGB2GRAY);
cvCopy(image_color[0], last_image_color[0], NULL);
cvCopy(image_color[1], last_image_color[1], NULL);
//Do the REAL VISION stuff first
for (int n = 0; n < FRAME_INTERVAL; n++)
{
for (int i = 0; i < NUM_CAMERAS; ++i)
{
cvCopy(image[i], last_image_track[i],NULL);
image_raw[i] = camera[i].get_frame();
cvRemap(image_raw[i], image_color[i], mx[i], my[i]);
cvCopy(image_color[i],image_raw[i],NULL);
//cvCopy(image_raw[i],image_color[i],NULL);
cvCvtColor(image_raw[i],image[i],CV_RGB2GRAY);
}
//Track each curve too (if last measurement was valid)
if (!reset_data_assoc)
{
curveMatcher[0].singleFrameTrack(last_image_track,image, roi[0]);
curveMatcher[1].singleFrameTrack(last_image_track,image, roi[0]);
}
counter++;
}
int n_pts_existing = 0;
int n_pts_new = 0;
double point_meas_existing[150];
double point_meas_new[150];
double planar_pose_meas[3];
int correspondences[50];
cvCopy(image_raw[0], image_color[0], NULL);
cvCopy(image_raw[1], image_color[1], NULL);
//use_points = true;
if(!first_time)
{
//Get point measurements (only if not first frame and previous curve measurement was invalid)
if (use_points)
pointFeatures->getPointMeasurements(&last_image[0],&image[0], &image_color[0], &point_meas_new[0],&n_pts_new,&point_meas_existing[0],&n_pts_existing, &correspondences[0], &planar_pose_meas[0]);
EKF->PredictKF(); //Also perform EKF predict step if not first time
}
//Find the edge points corresponding to curves in the images
CvPoint2D32f map_endpts[] = {curveMatcher[0].map_endpt_tracked,curveMatcher[1].map_endpt_tracked};
for (int i = 0; i < NUM_CAMERAS; ++i)
{
features[i].find_features(image_raw[i],seg[i],i,&(roi[i]),&map_endpts[0]);
curveMatcher[i].map_endpt_tracked = map_endpts[i];
}
#ifndef NO_SLAM
display_GUI->copy_images(&(image[0]));
for (int i = 0; i < 19; i++)
last_params[i] = params[i];
//GET EDGE POINTS AND GROUP THEM
//Extract edge points from both images
std::vector<CvPoint> ** featuresL =features[LEFT].return_features();
std::vector<CvPoint> ** featuresR =features[RIGHT].return_features();
//Below: hacky stuff to make the lengths the same, etc! (same amount of each curve observed in both images, etc)
int left_y_cutoff[] = {MIN(TOP_Y_CUTOFF,curveMatcher[0].map_endpt_tracked.y),MIN(TOP_Y_CUTOFF,curveMatcher[1].map_endpt_tracked.y)};
if(first_time)
{
left_y_cutoff[0] = TOP_Y_CUTOFF;
left_y_cutoff[1] = TOP_Y_CUTOFF;
}
CvMat * featuresLeftImage[2];
CvMat * featuresRightImage[2];
double tracked_endpt_y[] = {curveMatcher[0].map_endpt_tracked.y,curveMatcher[1].map_endpt_tracked.y};
//cout << "1\n";
edges_detected = curveFitter->cleanup_and_group_edges(featuresL,featuresR,&featuresLeftImage[0],&featuresRightImage[0], reset_data_assoc, &left_y_cutoff[0], &tracked_endpt_y[0]);
//cout << "2\n";
CvMat * state_current = EKF->getState();
//Only proceed if the above was successful and we have edges to work with
if (!edges_detected)
{
cout << "Edges not detected!\n";
valid_measurement = false;
}
else
{
double euler[3], euler_last[3];
double translation[3], translation_last[3];
double p[16], p_left[16], p_right[16];
double p_last[16], p_left_last[16], p_right_last[16];
//PERFORM CURVE FITTING AND STORE THE PARAMS IN 'params'
curveFitter->fit_curve(&(params[0]), featuresLeftImage, featuresRightImage, display_GUI);
//valid_measurement = EKF->CheckValidMeasurement(params[16],params[17],params[18],frames_since_good_measurement);
valid_measurement = true;
if (curveFitter->fitting_error > ERROR_THRESHOLD)
{
valid_measurement = false;
cout << "Curve fitting threshold exceeded!\n";
}
else
{
for (int i = 0; i < 19; i++)
{
if (isnan(params[i]))
{
valid_measurement = false;
cout << "Curve fitting produced NaN params!\n";
break;
}
}
}
for (int i = 0; i < 16; i++)
{
if (fabs(params[i]) > 50.0)
{
valid_measurement = false;
cout << "Curve fitting params out of range!\n";
break;
}
}
if (params[18] > 0.0)
{
valid_measurement = false;
cout << "Negative height from curve fitting!\n";
}
if(first_time)
valid_measurement = true;
double theta = params[16];
double phi = params[17];
double height = params[18];
if(valid_measurement)
{
euler[0] = 0.0;
euler[1] = params[16];
euler[2] = params[17];
translation[0] = 0.0;
translation[1] = 0.0;
translation[2] = params[18];
//Convert measured curve to image space, then display them on the images
control2coeffs(params,p);
control2coeffs(&(params[8]),&(p[8]));
poly_earth2image(&(p[0]), p_left, p_right, euler, translation);
poly_earth2image(&(p[8]), &(p_left[8]), &(p_right[8]), euler, translation);
euler_last[0] = 0.0;
euler_last[1] = last_params[16];
euler_last[2] = last_params[17];
translation_last[0] = 0.0;
translation_last[1] = 0.0;
translation_last[2] = last_params[18];
control2coeffs(last_params,p_last);
control2coeffs(&(last_params[8]),&(p_last[8]));
poly_earth2image(&(p_last[0]), p_left_last, p_right_last, euler_last, translation_last);
poly_earth2image(&(p_last[8]), &(p_left_last[8]), &(p_right_last[8]), euler_last, translation_last);
display_GUI->display_images(image[0], image[1], featuresLeftImage, featuresRightImage, p_left, p_right,image_color[0], image_color[1]);
// DETERMINE DATA ASSOCIATION (getMatchT) TO FIND THE T-VALUES TO SPLIT AT
for (int i = 0; i < 6; i++)
{
last_t_split[i] = t_split[i];
}
t_splitL = curveMatcher[0].getMatchT( featuresLeftImage[0], &(last_image[0]), &(last_image_track[0]),&(image[0]),&(last_image_color[0]),&(image_color[0]),&(last_params[0]), &(params[0]), 0, &left_assoc_flag, reset_data_assoc);
t_splitR = curveMatcher[1].getMatchT( featuresLeftImage[1], &(last_image[0]), &(last_image_track[0]),&(image[0]),&(last_image_color[0]),&(image_color[0]),&(last_params[0]), &(params[0]), 1, &right_assoc_flag, reset_data_assoc);
for (int i = 0; i < 3; i++)
{
t_split[2*i] = t_splitL[i];
t_split[2*i+1] = t_splitR[i];
}
//cout << "T SPLIT PTS\n";
//cout << t_split[0] << " " << t_split[2] << " "<< t_split[4] << " " << t_split[1] << " "<< t_split[3] << " " << t_split[5] << endl;
}
//Determine state based on data assoc parameter (if valid measurement)
if(valid_measurement && !first_time)
{
if (t_splitL[0] < -0.5)
{
left_assoc_flag = ONLY_ADD_STATE;
curveMatcher[0].updateMapCurves();
partial_curve_observed[0] = false;
}
else if (t_splitL[0] < 0.05 && t_splitL[1] > 0.95 && t_splitL[2] < 0.05)
{
if (partial_curve_observed[0])
{
left_assoc_flag = ONLY_UPDATE_ONE_STATE_PREV;
}
else
{
left_assoc_flag = ONLY_UPDATE_ONE_STATE;
}
}
else if (t_splitL[0] > 0.95 && t_splitL[1] < 0.05 && t_splitL[2] > 0.95)
{
if (partial_curve_observed[0])
{
left_assoc_flag = ONLY_UPDATE_ONE_STATE;
}
else
{
left_assoc_flag = ONLY_ADD_STATE;
}
partial_curve_observed[0] = false;
curveMatcher[0].updateMapCurves();
}
else
{
if(partial_curve_observed[0])
{
left_assoc_flag = UPDATE_TWO_STATES;
}
else
{
left_assoc_flag = ADD_AND_UPDATE_STATES;
}
partial_curve_observed[0] = true;
}
if (t_splitR[0] < -0.5)
{
right_assoc_flag = ONLY_ADD_STATE;
curveMatcher[1].updateMapCurves();
partial_curve_observed[1] = false;
}
else if (t_splitR[0] < 0.05 && t_splitR[1] > 0.95 && t_splitR[2] < 0.05)
{
if (partial_curve_observed[1])
{
right_assoc_flag = ONLY_UPDATE_ONE_STATE_PREV;
}
else
{
right_assoc_flag = ONLY_UPDATE_ONE_STATE;
}
}
else if (t_splitR[0] > 0.95 && t_splitR[1] < 0.05 && t_splitR[2] > 0.95)
{
if (partial_curve_observed[1])
{
right_assoc_flag = ONLY_UPDATE_ONE_STATE;
}
else
{
right_assoc_flag = ONLY_ADD_STATE;
}
partial_curve_observed[1] = false;
curveMatcher[1].updateMapCurves();
}
else
{
if(partial_curve_observed[1])
{
right_assoc_flag = UPDATE_TWO_STATES;
}
else
{
right_assoc_flag = ADD_AND_UPDATE_STATES;
}
partial_curve_observed[1] = true;
}
}
else if (first_time)
{
left_assoc_flag = ADD_FIRST_STATES;
right_assoc_flag = ADD_FIRST_STATES;
first_time = false;
}
//Plot features on images
for( int i = 0; i < featuresLeftImage[LEFT]->rows/2; i++)
{
cvCircle(image_color[LEFT],cvPoint(featuresLeftImage[LEFT]->data.db[2*i],featuresLeftImage[LEFT]->data.db[2*i+1]),1,CV_RGB(0,0,0));
}
for( int i = 0; i < featuresLeftImage[RIGHT]->rows/2; i++)
{
cvCircle(image_color[LEFT],cvPoint(featuresLeftImage[RIGHT]->data.db[2*i],featuresLeftImage[RIGHT]->data.db[2*i+1]),1,CV_RGB(0,0,0));
}
for( int i = 0; i < featuresRightImage[LEFT]->rows/2; i++)
{
cvCircle(image_color[RIGHT],cvPoint(featuresRightImage[LEFT]->data.db[2*i],featuresRightImage[LEFT]->data.db[2*i+1]),1,CV_RGB(0,0,0));
}
for( int i = 0; i < featuresRightImage[RIGHT]->rows/2; i++)
{
cvCircle(image_color[RIGHT],cvPoint(featuresRightImage[RIGHT]->data.db[2*i],featuresRightImage[RIGHT]->data.db[2*i+1]),1,CV_RGB(0,0,0));
}
cvShowImage("Left",image_color[LEFT]);
cvShowImage("Right",image_color[RIGHT]);
cvShowImage("Last Left",last_image_color[LEFT]);
cvShowImage("Last Right",last_image_color[RIGHT]);
//Figure out from data assoc what to do (state machine)
// Determine whether to just add states, or update, or both
if (left_assoc_flag == ADD_FIRST_STATES && right_assoc_flag == ADD_FIRST_STATES && valid_measurement)
{
for (int i = 0; i < 4; i++)
{
z16->data.db[i] = params[2*i];
z16->data.db[i+4] = params[2*i+1];
z16->data.db[i+8] = params[2*(i+4)];
z16->data.db[i+12] = params[2*(i+4)+1];
z->data.db[i] = params[2*i];
z->data.db[i+4] = params[2*i+1];
z->data.db[i+8] = params[2*(i+4)];
z->data.db[i+12] = params[2*(i+4)+1];
}
z16->data.db[16] = height;
z16->data.db[17] = phi;
z16->data.db[18] = theta;
EKF->AddFirstStates(z16);
state_limits.push_back(1.0);
state_limits.push_back(1.0);
left_curve_nums.push_back(0);
right_curve_nums.push_back(1);
num_map_curves+=2;
}
//Check if the measurement is valid, otherwise, ignore
else if (valid_measurement)
{
//Initialise update params (will be set as necessary))
int num_curves_to_update = 0;
curves_to_update.clear();
std::vector<CvMat *> correspondence_matrices;
CvMat * tempx = cvCreateMat(4,1,CV_64FC1);
CvMat * tempy = cvCreateMat(4,1,CV_64FC1);
//Depending on left and right assoc_flags, decide whether or not to split the measurement into two!
if (left_assoc_flag & (UPDATE_TWO_STATES|ADD_AND_UPDATE_STATES))
{
//Split left into two curves
for (int i = 0; i < 4; i++)
{
tempx->data.db[i] = params[2*i];
tempy->data.db[i] = params[2*i+1];
}
EKF->GetSplitMatrices(t_splitL[1],A1,A2);
cvMatMul(A1,tempx,z1); //Curve 1 x and y
cvMatMul(A1,tempy,z2);
cvMatMul(A2,tempx,z3); //Curve 2 x and y
cvMatMul(A2,tempy,z4);
for (int i = 0; i < 4; i++)
{
z_left->data.db[i] = z1->data.db[i];
z_left->data.db[i+4] = z2->data.db[i];
z_left->data.db[i+8] = z3->data.db[i];
z_left->data.db[i+12] = z4->data.db[i];
}
EKF->GetSplitMatrices(t_splitL[0],A1l,A2l);
EKF->GetSplitMatrices(t_splitL[2],B1l,B2l);
}
if (right_assoc_flag & (UPDATE_TWO_STATES|ADD_AND_UPDATE_STATES))
{
//Split RIGHT into two curves
for (int i = 0; i < 4; i++)
{
tempx->data.db[i] = params[2*i+8];
tempy->data.db[i] = params[2*i+9];
}
EKF->GetSplitMatrices(t_splitR[1],A1,A2);
cvMatMul(A1,tempx,z1); //Curve 1 x and y
cvMatMul(A1,tempy,z2);
cvMatMul(A2,tempx,z3); //Curve 2 x and y
cvMatMul(A2,tempy,z4);
for (int i = 0; i < 4; i++)
{
z_right->data.db[i] = z1->data.db[i];
z_right->data.db[i+4] = z2->data.db[i];
z_right->data.db[i+8] = z3->data.db[i];
z_right->data.db[i+12] = z4->data.db[i];
}
EKF->GetSplitMatrices(t_splitR[0],A1r,A2r);
EKF->GetSplitMatrices(t_splitR[2],B1r,B2r);
}
//UPDATE AND ADD LEFT CURVES
switch (left_assoc_flag)
{
case ONLY_ADD_STATE:
{
for (int i = 0; i < 4; i++)
{
z8->data.db[i] = params[2*i];
z8->data.db[i+4] = params[2*i+1];
z->data.db[i] = params[2*i];
z->data.db[i+4] = params[2*i+1];
}
EKF->AddNewCurve(z8,I4);
state_limits.push_back(1.0);
left_curve_nums.push_back(num_map_curves);
num_map_curves++;
break;
}
case ONLY_UPDATE_ONE_STATE:
{
for (int i = 0; i < 4; i++)
{
z->data.db[i+8*num_curves_to_update] = params[2*i];
z->data.db[i+4+8*num_curves_to_update] = params[2*i+1];
}
correspondence_matrices.push_back(I4);
state_limits.at(*(left_curve_nums.end()-1)) = 1.0;
curves_to_update.push_back(*(left_curve_nums.end()-1));
num_curves_to_update++;
break;
}
case ONLY_UPDATE_ONE_STATE_PREV:
{
for (int i = 0; i < 4; i++)
{
z->data.db[i+8*num_curves_to_update] = params[2*i];
z->data.db[i+4+8*num_curves_to_update] = params[2*i+1];
}
correspondence_matrices.push_back(I4);
state_limits.at(*(left_curve_nums.end()-2)) = 1.0;
curves_to_update.push_back(*(left_curve_nums.end()-2));
num_curves_to_update++;
break;
}
case ADD_AND_UPDATE_STATES:
{
//Add the first curve to 'update list'
for (int i = 0; i < 8; i++)
{
z->data.db[i+8*num_curves_to_update] = z_left->data.db[i];
}
correspondence_matrices.push_back(A2l);
state_limits.at(*(left_curve_nums.end()-1)) = 1.0;
curves_to_update.push_back(*(left_curve_nums.end()-1));
num_curves_to_update++;
//Add second curve as new state (but only if enough of it has been observed)
if (t_splitL[2] > CURVE_MIN_OBS)
{
for (int i = 0; i < 8; i++)
z8->data.db[i] = z_left->data.db[i+8];
EKF->AddNewCurve(z8,B1l);
state_limits.push_back(t_splitL[2]);
left_curve_nums.push_back(num_map_curves);
num_map_curves++;
}
else
partial_curve_observed[0] = false;
break;
}
case UPDATE_TWO_STATES:
{
for (int i = 0; i < 16; i++)
{
z->data.db[i+8*num_curves_to_update] = z_left->data.db[i];
}
correspondence_matrices.push_back(A2l);
correspondence_matrices.push_back(B1l);
curves_to_update.push_back(*(left_curve_nums.end()-2));
curves_to_update.push_back(*(left_curve_nums.end()-1));
state_limits.at(*(left_curve_nums.end()-2)) = 1.0;
state_limits.at(*(left_curve_nums.end()-1)) = t_splitL[2];
num_curves_to_update+=2;
break;
}
case DISCARD_MEASUREMENT:
{
break;
}
}
//UPDATE AND ADD RIGHT CURVES
switch (right_assoc_flag)
{
case ONLY_ADD_STATE:
{
for (int i = 0; i < 4; i++)
{
z8->data.db[i] = params[2*(i+4)];
z8->data.db[i+4] = params[2*(i+4)+1];
z->data.db[i+8] = params[2*(i+4)];
z->data.db[i+12] = params[2*(i+4)+1];
}
EKF->AddNewCurve(z8,I4);
state_limits.push_back(1.0);
right_curve_nums.push_back(num_map_curves);
num_map_curves++;
break;
}
case ONLY_UPDATE_ONE_STATE:
{
for (int i = 0; i < 4; i++)
{
z->data.db[i+8*num_curves_to_update] = params[2*(i+4)];
z->data.db[i+4+8*num_curves_to_update] = params[2*(i+4)+1];
}
correspondence_matrices.push_back(I4);
state_limits.at(*(right_curve_nums.end()-1)) = 1.0;
curves_to_update.push_back(*(right_curve_nums.end()-1));
num_curves_to_update++;
break;
}
case ONLY_UPDATE_ONE_STATE_PREV:
{
for (int i = 0; i < 4; i++)
{
z->data.db[i+8*num_curves_to_update] = params[2*(i+4)];
z->data.db[i+4+8*num_curves_to_update] = params[2*(i+4)+1];
}
correspondence_matrices.push_back(I4);
state_limits.at(*(right_curve_nums.end()-2)) = 1.0;
curves_to_update.push_back(*(right_curve_nums.end()-2));
num_curves_to_update++;
break;
}
case ADD_AND_UPDATE_STATES:
{
//Add the first curve to 'update list'
for (int i = 0; i < 8; i++)
{
z->data.db[i+8*num_curves_to_update] = z_right->data.db[i];
}
correspondence_matrices.push_back(A2r);
state_limits.at(*(right_curve_nums.end()-1)) = 1.0;
curves_to_update.push_back(*(right_curve_nums.end()-1));
num_curves_to_update++;
//Add second curve as new state (but only if enough of it has been observed)
if (t_splitR[2] > CURVE_MIN_OBS)
{
for (int i = 0; i < 8; i++)
z8->data.db[i] = z_right->data.db[i+8];
EKF->AddNewCurve(z8,B1r);
state_limits.push_back(t_splitR[2]);
right_curve_nums.push_back(num_map_curves);
num_map_curves++;
}
else
partial_curve_observed[1] = false;
break;
}
case UPDATE_TWO_STATES:
{
for (int i = 0; i < 16; i++)
{
z->data.db[i+8*num_curves_to_update] = z_right->data.db[i];
}
correspondence_matrices.push_back(A2r);
correspondence_matrices.push_back(B1r);
curves_to_update.push_back(*(right_curve_nums.end()-2));
curves_to_update.push_back(*(right_curve_nums.end()-1));
state_limits.at(*(right_curve_nums.end()-2)) = 1.0;
state_limits.at(*(right_curve_nums.end()-1)) = t_splitR[2];
num_curves_to_update+=2;
break;
}
case DISCARD_MEASUREMENT:
{
break;
}
}
//UPDATE EXISTING CURVES/POINTS IF NEEDED
if (num_curves_to_update > 0 || n_pts_existing > 0)
{
//num_curves_to_update = 0;
z->data.db[num_curves_to_update*8] = height;
z->data.db[num_curves_to_update*8+1] = phi;
z->data.db[num_curves_to_update*8+2] = theta;
//cout << "n pts existing: " << n_pts_existing << endl;
//n_pts_existing = MIN(10,n_pts_existing);
//EKF->UpdateNCurvesAndPoints(z, num_curves_to_update, &(correspondence_matrices),&(curves_to_update),&point_meas_existing[0],&correspondences[0],n_pts_existing);
EKF->UpdateNCurvesAndPoints(z, num_curves_to_update, &(correspondence_matrices),&(curves_to_update),&point_meas_existing[0],&correspondences[0],0);
//EKF->UpdatePoints(&point_meas_existing[0],&correspondences[0],n_pts_existing);
}
}
//UPDATE ONLY POINTS IF CURVES ARE A FAIL
if (n_pts_existing > 0)
EKF->UpdatePoints(&point_meas_existing[0],&correspondences[0],n_pts_existing);
curves_updated_last.clear();
for (int i = 0; i < curves_to_update.size(); i++)
curves_updated_last.push_back(curves_to_update.at(i));
/*cout << "Left curve nums: ";
for (int i = 0; i < left_curve_nums.size(); i++)
cout << left_curve_nums.at(i) << " ";
cout << endl;
cout << "Right curve nums: ";
for (int i = 0; i < right_curve_nums.size(); i++)
cout << right_curve_nums.at(i) << " ";
cout << endl;
cout << "Curves to update: ";
for (int i = 0; i < curves_to_update.size(); i++)
cout << curves_to_update[i] << " ";
cout << endl;*/
}
//Add any new point measurements we've made
EKF->AddNewPoints(&point_meas_new[0], n_pts_new);
//Display curves
state_current = EKF->getState();
display_GUI->generate_map(state_current,&state_limits,z, &(EKF->curve_inds), &(EKF->point_inds), EKF->num_curves, EKF->num_points);
//Print robot pose