Yo Fleyt
test morning
Dependencies: ISR_Mini-explorer mbed
Fork of
roboticLab_withclass_3_July
by 
Georgios Tsamis
Diff: MiniExplorerCoimbra.cpp
- Revision:
- 5:19f24c363418
- Parent:
- 3:37345c109dfc
- Child:
- 6:0e8db3a23486
--- a/MiniExplorerCoimbra.cpp Thu Jul 06 12:13:14 2017 +0000
+++ b/MiniExplorerCoimbra.cpp Thu Jul 06 16:51:40 2017 +0000
@@ -3,7 +3,7 @@
#define PI 3.14159
-MiniExplorerCoimbra::MiniExplorerCoimbra(float defaultXWorld, float defaultYWorld, float defaultThetaWorld, float widthRealMap, float heightRealMap):map(widthRealMap,heightRealMap,12,8),sonarLeft(10*PI/36,-4,4),sonarFront(0,0,5),sonarRight(-10*PI/36,4,4){
+MiniExplorerCoimbra::MiniExplorerCoimbra(float defaultXWorld, float defaultYWorld, float defaultThetaWorld, float widthRealMap, float heightRealMap):map(widthRealMap,heightRealMap,18,12),sonarLeft(10*PI/36,-4,4),sonarFront(0,0,5),sonarRight(-10*PI/36,4,4){
i2c1.frequency(100000);
initRobot(); //Initializing the robot
pc.baud(9600); // baud for the pc communication
@@ -21,12 +21,29 @@
this->kb=-13;
this->kv=200;
this->kh=200;
- this->kd=5;
+ this->kd=5;//previous 5
this->speed=300;
this->rangeForce=50;
- this->attractionConstantForce=200;
- this->repulsionConstantForce=-40000;
+ //not too bad values 200 and -40000
+ //not too bad values 200 and -20000
+ //not too bad values 500 and -20000
+ //not too bad values 500 and -25000 rangeForce 50
+ this->attractionConstantForce=600;
+ this->repulsionConstantForce=0;
+
+ this->covariancePositionEstimationK[0][0]=0;
+ this->covariancePositionEstimationK[0][1]=0;
+ this->covariancePositionEstimationK[0][2]=0;
+
+ this->covariancePositionEstimationK[1][0]=0;
+ this->covariancePositionEstimationK[1][1]=0;
+ this->covariancePositionEstimationK[1][2]=0;
+
+ this->covariancePositionEstimationK[2][0]=0;
+ this->covariancePositionEstimationK[2][1]=0;
+ this->covariancePositionEstimationK[2][2]=0;
+
}
void MiniExplorerCoimbra::setXYThetaAndXYThetaWorld(float defaultXWorld, float defaultYWorld, float defaultThetaWorld){
@@ -107,7 +124,7 @@
rightMotor(0,-angularRight);
}
- wait(0.5);
+ //wait(0.5);
} while(d>1);
//Stop at the end
@@ -118,7 +135,7 @@
void MiniExplorerCoimbra::test_procedure_lab2(int nbIteration){
for(int i=0;i<nbIteration;i++){
this->randomize_and_map();
- this->print_map_with_robot_position();
+ //this->print_map_with_robot_position();
}
while(1)
this->print_map_with_robot_position();
@@ -194,7 +211,7 @@
this->update_sonar_values(leftMm, frontMm, rightMm);
//Updating motor velocities
distanceToTarget=this->update_angular_speed_wheels_go_to_point_with_angle(targetXWorld,targetYWorld,targetAngleWorld,dt);
- wait(0.2);
+ //wait(0.2);
//Timer stuff
t.stop();
pc.printf("\n\rdist to target= %f",distanceToTarget);
@@ -224,7 +241,7 @@
//Updating motor velocities
distanceToTarget=this->update_angular_speed_wheels_go_to_point_with_angle(targetXWorld,targetYWorld,targetAngleWorld,dt);
- wait(0.2);
+ //wait(0.2);
//Timer stuff
t.stop();
pc.printf("\n\rdist to target= %f",distanceToTarget);
@@ -390,7 +407,7 @@
leftMotor(1,0);
rightMotor(1,0);
pc.printf("\r\n target reached");
- wait(3);//
+ //wait(3);//
}
void MiniExplorerCoimbra::vff(bool* reached, float targetXWorld, float targetYWorld){
@@ -467,13 +484,17 @@
pc.printf(" T ");
else{
currProba=this->map.log_to_proba(this->map.cellsLogValues[x][y]);
- if ( currProba < 0.5)
+ if ( currProba < 0.5){
pc.printf(" ");
- else{
- if(currProba==0.5)
+ //pc.printf("%f",currProba);
+ }else{
+ if(currProba==0.5){
pc.printf(" . ");
- else
+ //pc.printf("%f",currProba);
+ }else{
pc.printf(" X ");
+ //pc.printf("%f",currProba);
+ }
}
}
}
@@ -499,17 +520,22 @@
for (int x= 0; x<this->map.nbCellWidth; x++) {
heightIndiceInOrthonormal=this->map.cell_height_coordinate_to_world(y);
widthIndiceInOrthonormal=this->map.cell_width_coordinate_to_world(x);
- if(this->yWorld >= (heightIndiceInOrthonormal+heightMalus) && this->yWorld <= (heightIndiceInOrthonormal+heightBonus) && this->xWorld >= (widthIndiceInOrthonormal+widthMalus) && this->xWorld <= (widthIndiceInOrthonormal+widthBonus))
+ if(this->yWorld >= (heightIndiceInOrthonormal+heightMalus) && this->yWorld <= (heightIndiceInOrthonormal+heightBonus) && this->xWorld >= (widthIndiceInOrthonormal+widthMalus) && this->xWorld <= (widthIndiceInOrthonormal+widthBonus)){
pc.printf(" R ");
- else{
+ //pc.printf("%f",currProba);
+ }else{
currProba=this->map.log_to_proba(this->map.cellsLogValues[x][y]);
- if ( currProba < 0.5)
+ if ( currProba < 0.5){
pc.printf(" ");
- else{
- if(currProba==0.5)
+ //pc.printf("%f",currProba);
+ }else{
+ if(currProba==0.5){
pc.printf(" . ");
- else
- pc.printf(" X ");
+ //pc.printf("%f",currProba);
+ }else{
+ pc.printf(" X ");
+ //pc.printf("%f",currProba);
+ }
}
}
}
@@ -557,8 +583,8 @@
*forceXWorld=forceRepulsionComputedX;
*forceYWorld=forceRepulsionComputedY;
this->print_map_with_robot_position();
- pc.printf("\r\nForce X before:%f",*forceXWorld);
- pc.printf("\r\nForce Y before:%f",*forceYWorld);
+ pc.printf("\r\nForce X repul:%f",*forceXWorld);
+ pc.printf("\r\nForce Y repul:%f",*forceYWorld);
float distanceTargetRobot=sqrt(pow(targetXWorld-this->xWorld,2)+pow(targetYWorld-this->yWorld,2));
if(distanceTargetRobot != 0){
*forceXWorld+=-this->attractionConstantForce*(targetXWorld-this->xWorld)/distanceTargetRobot;
@@ -567,8 +593,8 @@
*forceXWorld+=-this->attractionConstantForce*(targetXWorld-this->xWorld)/0.01;
*forceYWorld+=-this->attractionConstantForce*(targetYWorld-this->yWorld)/0.01;
}
- pc.printf("\r\nForce X after:%f",*forceXWorld);
- pc.printf("\r\nForce Y after:%f",*forceYWorld);
+ pc.printf("\r\nForce X after attract:%f",*forceXWorld);
+ pc.printf("\r\nForce Y after attract:%f",*forceYWorld);
float amplitude=sqrt(pow(*forceXWorld,2)+pow(*forceYWorld,2));
if(amplitude!=0){//avoid division by 0 if forceX and forceY == 0
@@ -729,3 +755,583 @@
return abs((line_a*robot_x+line_b*robot_y+line_c)/sqrt(line_a*line_a+line_b*line_b));
}
+//4th LAB
+//starting position lower left
+
+void MiniExplorerCoimbra::test_procedure_lab_4(float sizeX, float sizeY, int nbRectangle){
+
+ this->map.fill_map_with_kalman_knowledge();
+
+ this->go_to_point_with_angle_kalman(this->xWorld+sizeX,this->yWorld,this->thetaWorld);
+
+ /*
+ for(int j=0;j<nbRectangle;j++){
+ //right
+ this->go_to_point_with_angle_kalman(this->xWorld+sizeX,this->yWorld,this->thetaWorld);
+ this->go_turn_kalman(this->xWorld,this->yWorld,this->thetaWorld+PI/2);
+
+ this->print_map_with_robot_position();
+ pc.printf("\n\rX= %f",this->xWorld);
+ pc.printf("\n\rY= %f",this->yWorld);
+ pc.printf("\n\rtheta= %f",this->thetaWorld);
+
+ //up
+ this->go_to_point_with_angle_kalman(this->xWorld+sizeX,this->yWorld+sizeY,this->thetaWorld);
+ this->go_turn_kalman(this->xWorld,this->yWorld,this->thetaWorld+PI/2);
+
+ this->print_map_with_robot_position();
+ pc.printf("\n\rX= %f",this->xWorld);
+ pc.printf("\n\rY= %f",this->yWorld);
+ pc.printf("\n\rtheta= %f",this->thetaWorld);
+ //left
+ this->go_to_point_with_angle_kalman(this->xWorld-sizeX,this->yWorld,this->thetaWorld);
+ this->go_turn_kalman(this->xWorld,this->yWorld,this->thetaWorld+PI/2);
+
+ this->print_map_with_robot_position();
+ pc.printf("\n\rX= %f",this->xWorld);
+ pc.printf("\n\rY= %f",this->yWorld);
+ pc.printf("\n\rtheta= %f",this->thetaWorld);
+ //down
+ this->go_to_point_with_angle_kalman(this->xWorld,this->yWorld-sizeY,this->thetaWorld);
+ this->go_turn_kalman(this->xWorld,this->yWorld,this->thetaWorld+PI/2);
+
+ this->print_map_with_robot_position();
+ pc.printf("\n\rX= %f",this->xWorld);
+ pc.printf("\n\rY= %f",this->yWorld);
+ pc.printf("\n\rtheta= %f",this->thetaWorld);
+
+ }
+ */
+}
+
+//move of targetXWorld and targetYWorld ending in a targetAngleWorld
+void MiniExplorerCoimbra::go_turn_kalman(float targetXWorld, float targetYWorld, float targetAngleWorld) {
+ //make sure the target is correct
+ if(targetAngleWorld > PI)
+ targetAngleWorld=-2*PI+targetAngleWorld;
+ if(targetAngleWorld < -PI)
+ targetAngleWorld=2*PI+targetAngleWorld;
+
+ float distanceToTarget=100;
+ do {
+ leftMotor(1,50);
+ rightMotor(0,50);
+ this->OdometriaKalmanFilter(1,1);
+
+ float distanceToTarget=this->dist(this->xWorld, this->yWorld, targetXWorld, targetYWorld);
+ //pc.printf("\n\rdist to target= %f",distanceToTarget);
+
+ } while(distanceToTarget>1 || (abs(targetAngleWorld-this->thetaWorld)>0.1));
+
+ //Stop at the end
+ leftMotor(1,0);
+ rightMotor(1,0);
+ pc.printf("\r\nReached Target!");
+}
+
+//move of targetXWorld and targetYWorld ending in a targetAngleWorld
+void MiniExplorerCoimbra::go_straight_kalman(float targetXWorld, float targetYWorld, float targetAngleWorld) {
+ //make sure the target is correct
+ if(targetAngleWorld > PI)
+ targetAngleWorld=-2*PI+targetAngleWorld;
+ if(targetAngleWorld < -PI)
+ targetAngleWorld=2*PI+targetAngleWorld;
+
+ float distanceToTarget=100;;
+
+ do {
+ leftMotor(1,400);
+ rightMotor(1,400);
+ this->OdometriaKalmanFilter(1,1);
+
+ float distanceToTarget=this->dist(this->xWorld, this->yWorld, targetXWorld, targetYWorld);
+ pc.printf("\n\rdist to target= %f",distanceToTarget);
+
+ } while(distanceToTarget>1 || (abs(targetAngleWorld-this->thetaWorld)>0.1));
+
+ //Stop at the end
+ leftMotor(1,0);
+ rightMotor(1,0);
+ pc.printf("\r\nReached Target!");
+}
+
+//move of targetXWorld and targetYWorld ending in a targetAngleWorld
+void MiniExplorerCoimbra::go_to_point_with_angle_kalman(float targetXWorld, float targetYWorld, float targetAngleWorld) {
+ float dt;
+ Timer t;
+ float distanceToTarget;
+ //make sure the target is correct
+ if(targetAngleWorld > PI)
+ targetAngleWorld=-2*PI+targetAngleWorld;
+ if(targetAngleWorld < -PI)
+ targetAngleWorld=2*PI+targetAngleWorld;
+
+ do {
+ //Timer stuff
+ dt = t.read();
+ t.reset();
+ t.start();
+
+ //Updating X,Y and theta with the odometry values
+ this->OdometriaKalmanFilter(1,1);
+
+ //Updating motor velocities
+ distanceToTarget=this->update_angular_speed_wheels_go_to_point_with_angle(targetXWorld,targetYWorld,targetAngleWorld,dt);
+
+ //wait(0.2);
+ //Timer stuff
+ t.stop();
+ pc.printf("\n\rdist to target= %f",distanceToTarget);
+
+ } while(distanceToTarget>1 || (abs(targetAngleWorld-this->thetaWorld)>0.1));
+
+ //Stop at the end
+ leftMotor(1,0);
+ rightMotor(1,0);
+ pc.printf("\r\nReached Target!");
+}
+
+void MiniExplorerCoimbra::OdometriaKalmanFilter(float encoderRightFailureRate,float encoderLeftFailureRate){
+ //=====KINEMATICS===========================
+ float R_cm;
+ float L_cm;
+
+ //fill R_cm and L_cm with how much is wheel has moved (custom robot.h)
+ OdometriaKalman(&R_cm, &L_cm);
+
+ encoderRightFailureRate=0.95;
+ encoderLeftFailureRate=1;
+
+ R_cm=R_cm*encoderRightFailureRate;
+ L_cm=L_cm*encoderLeftFailureRate;
+
+ float distanceMoved=(R_cm+L_cm)/2;
+ float angleMoved=(R_cm-L_cm)/this->distanceWheels;
+
+ float distanceMovedX=distanceMoved*cos(this->thetaWorld+angleMoved/2);
+ float distanceMovedY=distanceMoved*sin(this->thetaWorld+angleMoved/2);
+
+ //try with world coordinate system
+
+ float xEstimatedK=this->xWorld+distanceMovedX;
+ float yEstimatedK=this->yWorld+distanceMovedY;
+ float thetaWorldEstimatedK = this->thetaWorld+angleMoved;
+
+ //try with robot coordinate system
+ /*
+ float xEstimatedK=X;
+ float yEstimatedK=Y;
+ float thetaWorldEstimatedK = theta;
+ */
+ //=====ERROR_MODEL===========================
+
+ //FP Matrix
+ float Fp[3][3]={{1,0,0},{0,1,0},{0,0,1}};
+
+ Fp[0][2]=-1*distanceMoved*sin(this->thetaWorld+(angleMoved/2));
+ Fp[1][2]=distanceMoved*cos(this->thetaWorld+(angleMoved/2));
+
+ //Frl matrix
+ float Frl[3][2]={{0,0},{0,0},{(1/this->distanceWheels),-(1/this->distanceWheels)}};
+
+ Frl[0][0]=0.5*cos(this->thetaWorld+(angleMoved/2))-(distanceMoved/(2*this->distanceWheels))*sin(this->thetaWorld+(angleMoved/2));
+ Frl[0][1]=0.5*cos(this->thetaWorld+(angleMoved/2))+(distanceMoved/(2*this->distanceWheels))*sin(this->thetaWorld+(angleMoved/2));
+ Frl[1][0]=0.5*sin(this->thetaWorld+(angleMoved/2))+(distanceMoved/(2*this->distanceWheels))*cos(this->thetaWorld+(angleMoved/2));
+ Frl[1][1]=0.5*sin(this->thetaWorld+(angleMoved/2))-(distanceMoved/(2*this->distanceWheels))*cos(this->thetaWorld+(angleMoved/2));
+
+ //error constants...
+ float kr=1;
+ float kl=1;
+ float covar[2][2]={{kr*abs(R_cm), 0}, {0, kl*abs(L_cm)}};
+
+ //uncertainty positionx, and theta at
+ //1,1,1
+ float Q[3][3]={{1,0,0}, {0,2,0}, {0,0,0.01}};
+
+ covariancePositionEstimationK[0][0]=covar[0][0]*pow(Frl[0][0],2)+covar[1][1]*pow(Frl[0][1],2)+covariancePositionEstimationK[0][0]+Q[0][0]+covariancePositionEstimationK[2][0]*Fp[0][2]+Fp[0][2]*(covariancePositionEstimationK[0][2]+covariancePositionEstimationK[2][2]*Fp[0][2]);
+ covariancePositionEstimationK[0][1]=covariancePositionEstimationK[0][1]+covariancePositionEstimationK[2][1]*Fp[0][2]+Fp[1][2]*(covariancePositionEstimationK[0][2]+covariancePositionEstimationK[2][2]*Fp[0][2])+covar[0][0]*Frl[0][0]*Frl[1][0]+covar[1][1]*Frl[0][1];
+ covariancePositionEstimationK[0][2]=covariancePositionEstimationK[0][2]+covariancePositionEstimationK[2][2]*Fp[0][2]+covar[0][0]*Frl[0][0]*Frl[2][0]+covar[1][1]*Frl[0][1]*Frl[2][1];
+ covariancePositionEstimationK[1][0]=covariancePositionEstimationK[1][0]+covariancePositionEstimationK[2][0]*Fp[1][2]+Fp[0][2]*(covariancePositionEstimationK[1][2]+covariancePositionEstimationK[2][2]*Fp[1][2])+covar[0][0]*Frl[0][0]*Frl[1][0]+covar[1][1]*Frl[0][1]*Frl[1][1];
+ covariancePositionEstimationK[1][1]=covar[0][0]*pow(Frl[1][0],2)+covar[1][1]*pow(Frl[1][1],2)+covariancePositionEstimationK[1][1]+Q[1][1]+covariancePositionEstimationK[2][1]*Fp[1][2]+Fp[1][2]*(covariancePositionEstimationK[1][2]+covariancePositionEstimationK[2][2]*Fp[1][2]);
+ covariancePositionEstimationK[1][2]=covariancePositionEstimationK[1][2]+covariancePositionEstimationK[2][2]*Fp[1][2]+covar[0][0]*Frl[1][0]*Frl[2][0]+covar[1][1]*Frl[1][1]*Frl[2][1];
+ covariancePositionEstimationK[2][0]=covariancePositionEstimationK[2][0]+covariancePositionEstimationK[2][2]*Fp[0][2]+covar[0][0]*Frl[0][0]*Frl[2][0]+covar[1][1]*Frl[0][1]*Frl[2][1];
+ covariancePositionEstimationK[2][1]=covariancePositionEstimationK[2][1]+covariancePositionEstimationK[2][2]*Fp[1][2]+covar[0][0]*Frl[1][0]*Frl[2][0]+covar[1][1]*Frl[1][1]*Frl[2][1];
+ covariancePositionEstimationK[2][2]=covar[0][0]*pow(Frl[2][1],2)+covar[1][1]*pow(Frl[2][1],2)+covariancePositionEstimationK[2][2]+Q[2][2];
+
+ //=====OBSERVATION=====
+ //get the estimated measure we should have according to our knowledge of the map and the previously computed localisation
+
+ float leftCmEstimated=this->sonarLeft.maxRange;
+ float frontCmEstimated=this->sonarFront.maxRange;
+ float rightCmEstimated=this->sonarRight.maxRange;
+ float xWorldCell;
+ float yWorldCell;
+ float currDistance;
+ float xClosestCellLeft;
+ float yClosestCellLeft;
+ float xClosestCellFront;
+ float yClosestCellFront;
+ float xClosestCellRight;
+ float yClosestCellRight;
+ //get theorical distance to sonar
+ for(int i=0;i<this->map.nbCellWidth;i++){
+ for(int j=0;j<this->map.nbCellHeight;j++){
+ //check if occupied, if not discard
+ if(this->map.get_proba_cell(i,j)<0.5){
+ //check if in sonar range
+ xWorldCell=this->map.cell_width_coordinate_to_world(i);
+ yWorldCell=this->map.cell_height_coordinate_to_world(j);
+ //check left
+ currDistance=this->sonarLeft.isInRange(xWorldCell,yWorldCell,xEstimatedK,yEstimatedK,thetaWorldEstimatedK);
+ if((currDistance < this->sonarLeft.maxRange) && currDistance!=-1){
+ //check if distance is lower than previous, update lowest if so
+ if(currDistance < leftCmEstimated){
+ leftCmEstimated= currDistance;
+ xClosestCellLeft=xWorldCell;
+ yClosestCellLeft=yWorldCell;
+ }
+ }
+ //check front
+ currDistance=this->sonarFront.isInRange(xWorldCell,yWorldCell,xEstimatedK,yEstimatedK,thetaWorldEstimatedK);
+ if((currDistance < this->sonarFront.maxRange) && currDistance!=-1){
+ //check if distance is lower than previous, update lowest if so
+ if(currDistance < frontCmEstimated){
+ frontCmEstimated= currDistance;
+ xClosestCellFront=xWorldCell;
+ yClosestCellFront=yWorldCell;
+ }
+ }
+ //check right
+ currDistance=this->sonarRight.isInRange(xWorldCell,yWorldCell,xEstimatedK,yEstimatedK,thetaWorldEstimatedK);
+ if((currDistance < this->sonarRight.maxRange) && currDistance!=-1){
+ //check if distance is lower than previous, update lowest if so
+ if(currDistance < rightCmEstimated){
+ rightCmEstimated= currDistance;
+ xClosestCellRight=xWorldCell;
+ yClosestCellRight=yWorldCell;
+ }
+ }
+ }
+ }
+ }
+
+ //check measurements from sonars, see if they passed the validation gate
+ float leftCm = get_distance_left_sensor()/10;
+ float frontCm = get_distance_front_sensor()/10;
+ float rightCm = get_distance_right_sensor()/10;
+ //if superior to sonar range, put the value to sonar max range + 1
+ if(leftCm > this->sonarLeft.maxRange)
+ leftCm=this->sonarLeft.maxRange;
+ if(frontCm > this->sonarFront.maxRange)
+ frontCm=this->sonarFront.maxRange;
+ if(rightCm > this->sonarRight.maxRange)
+ rightCm=this->sonarRight.maxRange;
+
+ //======INNOVATION========
+ //get the innoncation: the value of the difference between the actual measure and what we anticipated
+ float innovationLeft=leftCm-leftCmEstimated;
+ float innovationFront=frontCm-frontCmEstimated;
+ float innovationRight=-rightCm-rightCmEstimated;
+ //compute jacobian of observation
+ float jacobianOfObservationLeft[1][3];
+ float jacobianOfObservationRight[1][3];
+ float jacobianOfObservationFront[1][3];
+ float xSonarLeft=xEstimatedK+this->sonarLeft.distanceX;
+ float ySonarLeft=yEstimatedK+this->sonarLeft.distanceY;
+ //left
+ jacobianOfObservationLeft[0][0]=(xSonarLeft-xClosestCellLeft)/leftCmEstimated;
+ jacobianOfObservationLeft[0][1]=(ySonarLeft-yClosestCellLeft)/leftCmEstimated;
+ jacobianOfObservationLeft[0][2]=(xClosestCellLeft-xSonarLeft)*(xSonarLeft*sin(thetaWorldEstimatedK)+ySonarLeft*cos(thetaWorldEstimatedK))+(yClosestCellLeft-ySonarLeft)*(-xSonarLeft*cos(thetaWorldEstimatedK)+ySonarLeft*sin(thetaWorldEstimatedK));
+ //front
+ float xSonarFront=xEstimatedK+this->sonarFront.distanceX;
+ float ySonarFront=yEstimatedK+this->sonarFront.distanceY;
+ jacobianOfObservationFront[0][0]=(xSonarFront-xClosestCellFront)/frontCmEstimated;
+ jacobianOfObservationFront[0][1]=(ySonarFront-yClosestCellFront)/frontCmEstimated;
+ jacobianOfObservationFront[0][2]=(xClosestCellFront-xSonarFront)*(xSonarFront*sin(thetaWorldEstimatedK)+ySonarFront*cos(thetaWorldEstimatedK))+(yClosestCellFront-ySonarFront)*(-xSonarFront*cos(thetaWorldEstimatedK)+ySonarFront*sin(thetaWorldEstimatedK));
+ //right
+ float xSonarRight=xEstimatedK+this->sonarRight.distanceX;
+ float ySonarRight=yEstimatedK+this->sonarRight.distanceY;
+ jacobianOfObservationRight[0][0]=(xSonarRight-xClosestCellRight)/rightCmEstimated;
+ jacobianOfObservationRight[0][1]=(ySonarRight-yClosestCellRight)/rightCmEstimated;
+ jacobianOfObservationRight[0][2]=(xClosestCellRight-xSonarRight)*(xSonarRight*sin(thetaWorldEstimatedK)+ySonarRight*cos(thetaWorldEstimatedK))+(yClosestCellRight-ySonarRight)*(-xSonarRight*cos(thetaWorldEstimatedK)+ySonarRight*sin(thetaWorldEstimatedK));
+
+ //error constants 0,0,0 sonars perfect; must be found by experimenting; gives mean and standanrt deviation
+ //let's assume
+ //in centimeters
+ float R_front=4;
+ float R_left=4;
+ float R_right=4;
+
+ //R-> 4 in diagonal
+
+ //S for each sonar (concatenated covariance matrix of innovation)
+ float innovationCovarianceFront=R_front+ jacobianOfObservationFront[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][2]) + jacobianOfObservationFront[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][2]) + jacobianOfObservationFront[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]);
+ float innovationCovarianceLeft=R_left+ jacobianOfObservationLeft[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationLeft[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationLeft[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]);
+ float innovationCovarianceRight=R_right+ jacobianOfObservationRight[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]);
+
+ //check if it pass the validation gate
+ float gateScoreLeft=innovationLeft*innovationLeft/innovationCovarianceLeft;
+ float gateScoreFront=innovationFront*innovationFront/innovationCovarianceFront;
+ float gateScoreRight=innovationRight*innovationRight/innovationCovarianceRight;
+ int leftPassed=0;
+ int frontPassed=0;
+ int rightPassed=0;
+
+ //5cm -> 25
+ int errorsquare=25;//constant error
+
+ if(gateScoreLeft <= errorsquare)
+ leftPassed=1;
+ if(gateScoreFront <= errorsquare)
+ frontPassed=10;
+ if(gateScoreRight <= errorsquare)
+ rightPassed=100;
+ //for those who passed
+ //compute composite innovation
+ int nbPassed=leftPassed+frontPassed+rightPassed;
+
+ float xEstimatedKNext=xEstimatedK;
+ float yEstimatedKNext=xEstimatedK;
+ float thetaWorldEstimatedKNext=thetaWorldEstimatedK;
+
+ float compositeInnovationCovariance3x3[3][3]={{0,0,0}, {0,0,0}, {0,0,0}};
+
+ float compositeInnovationCovariance2x2[2][2]={{0,0}, {0,0}};
+
+ float compositeInnovationCovariance1x1=0;
+
+ float kalmanGain3X1[3][1]={{0}, {0}, {0}};
+ float kalmanGain3X2[3][2]={{0,0}, {0.0}, {0,0}};
+ float kalmanGain3X3[3][3]={{0,0,0}, {0,0,0}, {0,0,0}};
+
+ //we do not use the composite measurement jacobian (16), we directly use the values from the measurement jacobian (jacobianOfObservation)
+
+ switch(nbPassed){
+ case 0://none
+ //nothings happens it's okay
+ break;
+ case 1://left
+ compositeInnovationCovariance1x1=R_right + jacobianOfObservationRight[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]);
+
+ kalmanGain3X1[0][0]=(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2])/compositeInnovationCovariance1x1;
+ kalmanGain3X1[1][0]=(covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2])/compositeInnovationCovariance1x1;
+ kalmanGain3X1[2][0]=(covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2])/compositeInnovationCovariance1x1;
+
+ xEstimatedKNext+= kalmanGain3X1[0][0]*innovationRight;
+ yEstimatedKNext+= kalmanGain3X1[1][0]*innovationRight;
+ thetaWorldEstimatedKNext+= kalmanGain3X1[2][0]*innovationRight;
+
+ covariancePositionEstimationK[0][0]=- compositeInnovationCovariance1x1*pow(kalmanGain3X1[0][0],2) + covariancePositionEstimationK[0][0];
+ covariancePositionEstimationK[0][1]=covariancePositionEstimationK[0][1] - kalmanGain3X1[0][0]*kalmanGain3X1[1][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[0][2]=covariancePositionEstimationK[0][2] - kalmanGain3X1[0][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[1][0]=covariancePositionEstimationK[1][0] - kalmanGain3X1[0][0]*kalmanGain3X1[1][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[1][1]=- compositeInnovationCovariance1x1*pow(kalmanGain3X1[1][0],2) + covariancePositionEstimationK[1][1];
+ covariancePositionEstimationK[1][2]=covariancePositionEstimationK[1][2] - kalmanGain3X1[1][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[2][0]=covariancePositionEstimationK[2][0] - kalmanGain3X1[0][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[2][1]=covariancePositionEstimationK[2][1] - kalmanGain3X1[1][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[2][2]=- compositeInnovationCovariance1x1*pow(kalmanGain3X1[2][0],2) + covariancePositionEstimationK[2][2];
+
+ break;
+ case 10://front
+
+ compositeInnovationCovariance1x1=R_front + jacobianOfObservationFront[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][2]) + jacobianOfObservationFront[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][2]) + jacobianOfObservationFront[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]);
+
+ kalmanGain3X1[0][0]=(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][2])/compositeInnovationCovariance1x1;
+ kalmanGain3X1[1][0]=(covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][2])/compositeInnovationCovariance1x1;
+ kalmanGain3X1[2][0]=(covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2])/compositeInnovationCovariance1x1;
+
+ xEstimatedKNext+= kalmanGain3X1[0][0]*innovationFront;
+ yEstimatedKNext+= kalmanGain3X1[1][0]*innovationFront;
+ thetaWorldEstimatedKNext+= kalmanGain3X1[2][0]*innovationFront;
+
+ covariancePositionEstimationK[0][0]=- compositeInnovationCovariance1x1*pow(kalmanGain3X1[0][0],2) + covariancePositionEstimationK[0][0];
+ covariancePositionEstimationK[0][1]=covariancePositionEstimationK[0][1] - kalmanGain3X1[0][0]*kalmanGain3X1[1][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[0][2]=covariancePositionEstimationK[0][2] - kalmanGain3X1[0][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[1][0]=covariancePositionEstimationK[1][0] - kalmanGain3X1[0][0]*kalmanGain3X1[1][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[1][1]=- compositeInnovationCovariance1x1*pow(kalmanGain3X1[1][0],2) + covariancePositionEstimationK[1][1];
+ covariancePositionEstimationK[1][2]=covariancePositionEstimationK[1][2] - kalmanGain3X1[1][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[2][0]=covariancePositionEstimationK[2][0] - kalmanGain3X1[0][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[2][1]=covariancePositionEstimationK[2][1] - kalmanGain3X1[1][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[2][2]=- compositeInnovationCovariance1x1*pow(kalmanGain3X1[2][0],2) + covariancePositionEstimationK[2][2];
+
+ break;
+ case 11://left and front
+ compositeInnovationCovariance2x2[0][0]=R_front + jacobianOfObservationFront[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][2]) + jacobianOfObservationFront[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][2]) + jacobianOfObservationFront[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]);
+ compositeInnovationCovariance2x2[0][1]=jacobianOfObservationLeft[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][2]) + jacobianOfObservationLeft[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][2]) + jacobianOfObservationLeft[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]);
+ compositeInnovationCovariance2x2[1][0]=jacobianOfObservationFront[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationFront[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationFront[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]);
+ compositeInnovationCovariance2x2[1][1]=R_left + jacobianOfObservationLeft[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationLeft[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationLeft[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]);
+
+ kalmanGain3X2[0][0]=(compositeInnovationCovariance2x2[1][1]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[1][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[0][1]=(compositeInnovationCovariance2x2[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[0][1]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[1][0]=(compositeInnovationCovariance2x2[1][1]*(covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[1][0]*(covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[1][1]=(compositeInnovationCovariance2x2[0][0]*(covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[0][1]*(covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[2][0]=(compositeInnovationCovariance2x2[1][1]*(covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[1][0]*(covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[2][1]=(compositeInnovationCovariance2x2[0][0]*(covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[0][1]*(covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+
+ xEstimatedKNext+= kalmanGain3X2[0][0]*innovationFront + kalmanGain3X2[0][1]*innovationLeft;
+ yEstimatedKNext+= kalmanGain3X2[1][0]*innovationFront + kalmanGain3X2[1][1]*innovationLeft;
+ thetaWorldEstimatedKNext+= kalmanGain3X2[2][0]*innovationFront + kalmanGain3X2[2][1]*innovationLeft;
+
+ covariancePositionEstimationK[0][0]=covariancePositionEstimationK[0][0] - kalmanGain3X2[0][0]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[0][1]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[0][1]=covariancePositionEstimationK[0][1] - kalmanGain3X2[1][0]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[1][1]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[0][2]=covariancePositionEstimationK[0][2] - kalmanGain3X2[2][0]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[2][1]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[1][0]=covariancePositionEstimationK[1][0] - kalmanGain3X2[0][0]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[0][1]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[1][1]=covariancePositionEstimationK[1][1] - kalmanGain3X2[1][0]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[1][1]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[1][2]=covariancePositionEstimationK[1][2] - kalmanGain3X2[2][0]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[2][1]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[2][0]=covariancePositionEstimationK[2][0] - kalmanGain3X2[0][0]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[0][1]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[2][1]=covariancePositionEstimationK[2][1] - kalmanGain3X2[1][0]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[1][1]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[2][2]=covariancePositionEstimationK[2][2] - kalmanGain3X2[2][0]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[2][1]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][1]);
+
+ break;
+ case 100://right
+
+ compositeInnovationCovariance1x1=R_right + jacobianOfObservationRight[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]);
+
+ kalmanGain3X1[0][0]=(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2])/compositeInnovationCovariance1x1;
+ kalmanGain3X1[1][0]=(covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2])/compositeInnovationCovariance1x1;
+ kalmanGain3X1[2][0]=(covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2])/compositeInnovationCovariance1x1;
+
+ xEstimatedKNext+= kalmanGain3X1[0][0]*innovationRight;
+ yEstimatedKNext+= kalmanGain3X1[1][0]*innovationRight;
+ thetaWorldEstimatedKNext+= kalmanGain3X1[2][0]*innovationRight;
+
+ covariancePositionEstimationK[0][0]=- compositeInnovationCovariance1x1*pow(kalmanGain3X1[0][0],2) + covariancePositionEstimationK[0][0];
+ covariancePositionEstimationK[0][1]=covariancePositionEstimationK[0][1] - kalmanGain3X1[0][0]*kalmanGain3X1[1][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[0][2]=covariancePositionEstimationK[0][2] - kalmanGain3X1[0][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[1][0]=covariancePositionEstimationK[1][0] - kalmanGain3X1[0][0]*kalmanGain3X1[1][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[1][1]=- compositeInnovationCovariance1x1*pow(kalmanGain3X1[1][0],2) + covariancePositionEstimationK[1][1];
+ covariancePositionEstimationK[1][2]=covariancePositionEstimationK[1][2] - kalmanGain3X1[1][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[2][0]=covariancePositionEstimationK[2][0] - kalmanGain3X1[0][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[2][1]=covariancePositionEstimationK[2][1] - kalmanGain3X1[1][0]*kalmanGain3X1[2][0]*compositeInnovationCovariance1x1;
+ covariancePositionEstimationK[2][2]=- compositeInnovationCovariance1x1*pow(kalmanGain3X1[2][0],2) + covariancePositionEstimationK[2][2];
+
+ break;
+ case 101://right and left
+ compositeInnovationCovariance2x2[0][0]=R_left + jacobianOfObservationLeft[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationLeft[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationLeft[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]);
+ compositeInnovationCovariance2x2[0][1]=jacobianOfObservationRight[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationRight[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationRight[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]);
+ compositeInnovationCovariance2x2[1][0]=jacobianOfObservationLeft[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][2]) + jacobianOfObservationLeft[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][2]) + jacobianOfObservationLeft[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]);
+ compositeInnovationCovariance2x2[1][1]=R_right + jacobianOfObservationRight[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]);
+
+ kalmanGain3X2[0][0]=(compositeInnovationCovariance2x2[1][1]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[1][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[0][1]=(compositeInnovationCovariance2x2[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[0][1]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[1][0]=(compositeInnovationCovariance2x2[1][1]*(covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[1][0]*(covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[1][1]=(compositeInnovationCovariance2x2[0][0]*(covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[0][1]*(covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[2][0]=(compositeInnovationCovariance2x2[1][1]*(covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[1][0]*(covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[2][1]=(compositeInnovationCovariance2x2[0][0]*(covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[0][1]*(covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+
+ xEstimatedKNext+= kalmanGain3X2[0][0]*innovationLeft + kalmanGain3X2[0][1]*innovationRight;
+ yEstimatedKNext+= kalmanGain3X2[1][0]*innovationLeft + kalmanGain3X2[1][1]*innovationRight;
+ thetaWorldEstimatedKNext+= kalmanGain3X2[2][0]*innovationLeft + kalmanGain3X2[2][1]*innovationRight;
+
+ covariancePositionEstimationK[0][0]=covariancePositionEstimationK[0][0] - kalmanGain3X2[0][0]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[0][1]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[0][1]=covariancePositionEstimationK[0][1] - kalmanGain3X2[1][0]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[1][1]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[0][2]=covariancePositionEstimationK[0][2] - kalmanGain3X2[2][0]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[2][1]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[1][0]=covariancePositionEstimationK[1][0] - kalmanGain3X2[0][0]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[0][1]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[1][1]=covariancePositionEstimationK[1][1] - kalmanGain3X2[1][0]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[1][1]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[1][2]=covariancePositionEstimationK[1][2] - kalmanGain3X2[2][0]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[2][1]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[2][0]=covariancePositionEstimationK[2][0] - kalmanGain3X2[0][0]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[0][1]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[2][1]=covariancePositionEstimationK[2][1] - kalmanGain3X2[1][0]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[1][1]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[2][2]=covariancePositionEstimationK[2][2] - kalmanGain3X2[2][0]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[2][1]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][1]);
+
+ break;
+ case 110://right and front
+
+ compositeInnovationCovariance2x2[0][0]=R_front + jacobianOfObservationFront[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][2]) + jacobianOfObservationFront[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][2]) + jacobianOfObservationFront[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]);
+ compositeInnovationCovariance2x2[0][1]=jacobianOfObservationRight[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][2]) + jacobianOfObservationRight[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][2]) + jacobianOfObservationRight[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]);
+ compositeInnovationCovariance2x2[1][0]=jacobianOfObservationFront[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][2]) + jacobianOfObservationFront[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][2]) + jacobianOfObservationFront[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]);
+ compositeInnovationCovariance2x2[1][1]=R_right + jacobianOfObservationRight[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]);
+
+ kalmanGain3X2[0][0]=(compositeInnovationCovariance2x2[1][1]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[1][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[0][1]=(compositeInnovationCovariance2x2[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[0][1]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[1][0]=(compositeInnovationCovariance2x2[1][1]*(covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[1][0]*(covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[1][1]=(compositeInnovationCovariance2x2[0][0]*(covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[0][1]*(covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[2][0]=(compositeInnovationCovariance2x2[1][1]*(covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[1][0]*(covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+ kalmanGain3X2[2][1]=(compositeInnovationCovariance2x2[0][0]*(covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]) - (compositeInnovationCovariance2x2[0][1]*(covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]))/(compositeInnovationCovariance2x2[0][0]*compositeInnovationCovariance2x2[1][1] - compositeInnovationCovariance2x2[0][1]*compositeInnovationCovariance2x2[1][0]);
+
+ xEstimatedKNext+= kalmanGain3X2[0][0]*innovationFront + kalmanGain3X2[0][1]*innovationRight;
+ yEstimatedKNext+= kalmanGain3X2[1][0]*innovationFront + kalmanGain3X2[1][1]*innovationRight;
+ thetaWorldEstimatedKNext+= kalmanGain3X2[2][0]*innovationFront + kalmanGain3X2[2][1]*innovationRight;
+
+ covariancePositionEstimationK[0][0]=covariancePositionEstimationK[0][0] - kalmanGain3X2[0][0]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[0][1]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[0][1]=covariancePositionEstimationK[0][1] - kalmanGain3X2[1][0]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[1][1]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[0][2]=covariancePositionEstimationK[0][2] - kalmanGain3X2[2][0]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[2][1]*(kalmanGain3X2[0][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[0][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[1][0]=covariancePositionEstimationK[1][0] - kalmanGain3X2[0][0]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[0][1]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[1][1]=covariancePositionEstimationK[1][1] - kalmanGain3X2[1][0]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[1][1]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[1][2]=covariancePositionEstimationK[1][2] - kalmanGain3X2[2][0]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[2][1]*(kalmanGain3X2[1][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[1][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[2][0]=covariancePositionEstimationK[2][0] - kalmanGain3X2[0][0]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[0][1]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[2][1]=covariancePositionEstimationK[2][1] - kalmanGain3X2[1][0]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[1][1]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][1]);
+ covariancePositionEstimationK[2][2]=covariancePositionEstimationK[2][2] - kalmanGain3X2[2][0]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][0] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][0]) - kalmanGain3X2[2][1]*(kalmanGain3X2[2][0]*compositeInnovationCovariance2x2[0][1] + kalmanGain3X2[2][1]*compositeInnovationCovariance2x2[1][1]);
+
+ break;
+ case 111://right front and left
+ //get the compositeInnovationCovariance3x3
+ compositeInnovationCovariance3x3[0][0]=R_front + jacobianOfObservationFront[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][2]) + jacobianOfObservationFront[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][2]) + jacobianOfObservationFront[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]);
+ compositeInnovationCovariance3x3[0][1]=jacobianOfObservationLeft[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][2]) + jacobianOfObservationLeft[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][2]) + jacobianOfObservationLeft[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]);
+ compositeInnovationCovariance3x3[0][2]=jacobianOfObservationRight[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][2]) + jacobianOfObservationRight[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][2]) + jacobianOfObservationRight[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]);
+ compositeInnovationCovariance3x3[1][0]=jacobianOfObservationFront[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationFront[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationFront[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]);
+ compositeInnovationCovariance3x3[1][1]=R_left + jacobianOfObservationLeft[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationLeft[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationLeft[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]);
+ compositeInnovationCovariance3x3[1][2]=jacobianOfObservationRight[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationRight[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][2]) + jacobianOfObservationRight[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]);
+ compositeInnovationCovariance3x3[2][0]=jacobianOfObservationFront[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][2]) + jacobianOfObservationFront[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][2]) + jacobianOfObservationFront[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]);
+ compositeInnovationCovariance3x3[2][1]=jacobianOfObservationLeft[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][2]) + jacobianOfObservationLeft[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][2]) + jacobianOfObservationLeft[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]);
+ compositeInnovationCovariance3x3[2][2]=R_right + jacobianOfObservationRight[0][0]*(covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][1]*(covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][2]) + jacobianOfObservationRight[0][2]*(covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]);
+
+ //compute the kalman gain
+ kalmanGain3X3[0][0]=(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0])/(compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0]);
+ kalmanGain3X3[0][1]=-(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][0])/(compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0]);
+ kalmanGain3X3[0][2]=(covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2] - covariancePositionEstimationK[0][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1] + covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2] - covariancePositionEstimationK[0][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1] + covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2] - covariancePositionEstimationK[0][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2] + covariancePositionEstimationK[0][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0] - covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2] + covariancePositionEstimationK[0][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0] - covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2] + covariancePositionEstimationK[0][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0] + covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[0][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0] + covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[0][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0] + covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[0][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0])/(compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0]);
+ kalmanGain3X3[1][0]=(covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0])/(compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0]);
+ kalmanGain3X3[1][1]=-(covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][0])/(compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0]);
+ kalmanGain3X3[1][2]=(covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2] - covariancePositionEstimationK[1][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1] + covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2] - covariancePositionEstimationK[1][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1] + covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2] - covariancePositionEstimationK[1][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2] + covariancePositionEstimationK[1][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0] - covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2] + covariancePositionEstimationK[1][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0] - covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2] + covariancePositionEstimationK[1][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0] + covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[1][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0] + covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[1][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0] + covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[1][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0])/(compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0]);
+ kalmanGain3X3[2][0]=(covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0])/(compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0]);
+ kalmanGain3X3[2][1]=-(covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][2] - covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][0] - covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][2] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][0] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[2][1] - covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[2][0])/(compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0]);
+ kalmanGain3X3[2][2]=(covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2] - covariancePositionEstimationK[2][0]*jacobianOfObservationFront[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1] + covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2] - covariancePositionEstimationK[2][1]*jacobianOfObservationFront[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1] + covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2] - covariancePositionEstimationK[2][2]*jacobianOfObservationFront[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2] + covariancePositionEstimationK[2][0]*jacobianOfObservationLeft[0][0]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0] - covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2] + covariancePositionEstimationK[2][1]*jacobianOfObservationLeft[0][1]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0] - covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2] + covariancePositionEstimationK[2][2]*jacobianOfObservationLeft[0][2]*compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0] + covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[2][0]*jacobianOfObservationRight[0][0]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0] + covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[2][1]*jacobianOfObservationRight[0][1]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0] + covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1] - covariancePositionEstimationK[2][2]*jacobianOfObservationRight[0][2]*compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0])/(compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][2] - compositeInnovationCovariance3x3[0][0]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][2] + compositeInnovationCovariance3x3[0][1]*compositeInnovationCovariance3x3[1][2]*compositeInnovationCovariance3x3[2][0] + compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][0]*compositeInnovationCovariance3x3[2][1] - compositeInnovationCovariance3x3[0][2]*compositeInnovationCovariance3x3[1][1]*compositeInnovationCovariance3x3[2][0]);
+
+ //update the prediction
+ xEstimatedKNext+= kalmanGain3X3[0][0]*innovationFront + kalmanGain3X3[0][1]*innovationLeft + kalmanGain3X3[0][2]*innovationRight;
+ yEstimatedKNext+= kalmanGain3X3[1][0]*innovationFront + kalmanGain3X3[1][1]*innovationLeft + kalmanGain3X3[1][2]*innovationRight;
+ thetaWorldEstimatedKNext+= kalmanGain3X3[2][0]*innovationFront + kalmanGain3X3[2][1]*innovationLeft + kalmanGain3X3[2][2]*innovationRight;
+
+ //update covariancePositionEstimationK
+ covariancePositionEstimationK[0][0]=covariancePositionEstimationK[0][0] - kalmanGain3X3[0][0]*(kalmanGain3X3[0][0]*compositeInnovationCovariance3x3[0][0] + kalmanGain3X3[0][1]*compositeInnovationCovariance3x3[1][0] + kalmanGain3X3[0][2]*compositeInnovationCovariance3x3[2][0]) - kalmanGain3X3[0][1]*(kalmanGain3X3[0][0]*compositeInnovationCovariance3x3[0][1] + kalmanGain3X3[0][1]*compositeInnovationCovariance3x3[1][1] + kalmanGain3X3[0][2]*compositeInnovationCovariance3x3[2][1]) - kalmanGain3X3[0][2]*(kalmanGain3X3[0][0]*compositeInnovationCovariance3x3[0][2] + kalmanGain3X3[0][1]*compositeInnovationCovariance3x3[1][2] + kalmanGain3X3[0][2]*compositeInnovationCovariance3x3[2][2]);
+ covariancePositionEstimationK[0][1]=covariancePositionEstimationK[0][1] - kalmanGain3X3[1][0]*(kalmanGain3X3[0][0]*compositeInnovationCovariance3x3[0][0] + kalmanGain3X3[0][1]*compositeInnovationCovariance3x3[1][0] + kalmanGain3X3[0][2]*compositeInnovationCovariance3x3[2][0]) - kalmanGain3X3[1][1]*(kalmanGain3X3[0][0]*compositeInnovationCovariance3x3[0][1] + kalmanGain3X3[0][1]*compositeInnovationCovariance3x3[1][1] + kalmanGain3X3[0][2]*compositeInnovationCovariance3x3[2][1]) - kalmanGain3X3[1][2]*(kalmanGain3X3[0][0]*compositeInnovationCovariance3x3[0][2] + kalmanGain3X3[0][1]*compositeInnovationCovariance3x3[1][2] + kalmanGain3X3[0][2]*compositeInnovationCovariance3x3[2][2]);
+ covariancePositionEstimationK[0][2]=covariancePositionEstimationK[0][2] - kalmanGain3X3[2][0]*(kalmanGain3X3[0][0]*compositeInnovationCovariance3x3[0][0] + kalmanGain3X3[0][1]*compositeInnovationCovariance3x3[1][0] + kalmanGain3X3[0][2]*compositeInnovationCovariance3x3[2][0]) - kalmanGain3X3[2][1]*(kalmanGain3X3[0][0]*compositeInnovationCovariance3x3[0][1] + kalmanGain3X3[0][1]*compositeInnovationCovariance3x3[1][1] + kalmanGain3X3[0][2]*compositeInnovationCovariance3x3[2][1]) - kalmanGain3X3[2][2]*(kalmanGain3X3[0][0]*compositeInnovationCovariance3x3[0][2] + kalmanGain3X3[0][1]*compositeInnovationCovariance3x3[1][2] + kalmanGain3X3[0][2]*compositeInnovationCovariance3x3[2][2]);
+ covariancePositionEstimationK[1][0]=covariancePositionEstimationK[1][0] - kalmanGain3X3[0][0]*(kalmanGain3X3[1][0]*compositeInnovationCovariance3x3[0][0] + kalmanGain3X3[1][1]*compositeInnovationCovariance3x3[1][0] + kalmanGain3X3[1][2]*compositeInnovationCovariance3x3[2][0]) - kalmanGain3X3[0][1]*(kalmanGain3X3[1][0]*compositeInnovationCovariance3x3[0][1] + kalmanGain3X3[1][1]*compositeInnovationCovariance3x3[1][1] + kalmanGain3X3[1][2]*compositeInnovationCovariance3x3[2][1]) - kalmanGain3X3[0][2]*(kalmanGain3X3[1][0]*compositeInnovationCovariance3x3[0][2] + kalmanGain3X3[1][1]*compositeInnovationCovariance3x3[1][2] + kalmanGain3X3[1][2]*compositeInnovationCovariance3x3[2][2]);
+ covariancePositionEstimationK[1][1]=covariancePositionEstimationK[1][1] - kalmanGain3X3[1][0]*(kalmanGain3X3[1][0]*compositeInnovationCovariance3x3[0][0] + kalmanGain3X3[1][1]*compositeInnovationCovariance3x3[1][0] + kalmanGain3X3[1][2]*compositeInnovationCovariance3x3[2][0]) - kalmanGain3X3[1][1]*(kalmanGain3X3[1][0]*compositeInnovationCovariance3x3[0][1] + kalmanGain3X3[1][1]*compositeInnovationCovariance3x3[1][1] + kalmanGain3X3[1][2]*compositeInnovationCovariance3x3[2][1]) - kalmanGain3X3[1][2]*(kalmanGain3X3[1][0]*compositeInnovationCovariance3x3[0][2] + kalmanGain3X3[1][1]*compositeInnovationCovariance3x3[1][2] + kalmanGain3X3[1][2]*compositeInnovationCovariance3x3[2][2]);
+ covariancePositionEstimationK[1][2]=covariancePositionEstimationK[1][2] - kalmanGain3X3[2][0]*(kalmanGain3X3[1][0]*compositeInnovationCovariance3x3[0][0] + kalmanGain3X3[1][1]*compositeInnovationCovariance3x3[1][0] + kalmanGain3X3[1][2]*compositeInnovationCovariance3x3[2][0]) - kalmanGain3X3[2][1]*(kalmanGain3X3[1][0]*compositeInnovationCovariance3x3[0][1] + kalmanGain3X3[1][1]*compositeInnovationCovariance3x3[1][1] + kalmanGain3X3[1][2]*compositeInnovationCovariance3x3[2][1]) - kalmanGain3X3[2][2]*(kalmanGain3X3[1][0]*compositeInnovationCovariance3x3[0][2] + kalmanGain3X3[1][1]*compositeInnovationCovariance3x3[1][2] + kalmanGain3X3[1][2]*compositeInnovationCovariance3x3[2][2]);
+ covariancePositionEstimationK[2][0]=covariancePositionEstimationK[2][0] - kalmanGain3X3[0][0]*(kalmanGain3X3[2][0]*compositeInnovationCovariance3x3[0][0] + kalmanGain3X3[2][1]*compositeInnovationCovariance3x3[1][0] + kalmanGain3X3[2][2]*compositeInnovationCovariance3x3[2][0]) - kalmanGain3X3[0][1]*(kalmanGain3X3[2][0]*compositeInnovationCovariance3x3[0][1] + kalmanGain3X3[2][1]*compositeInnovationCovariance3x3[1][1] + kalmanGain3X3[2][2]*compositeInnovationCovariance3x3[2][1]) - kalmanGain3X3[0][2]*(kalmanGain3X3[2][0]*compositeInnovationCovariance3x3[0][2] + kalmanGain3X3[2][1]*compositeInnovationCovariance3x3[1][2] + kalmanGain3X3[2][2]*compositeInnovationCovariance3x3[2][2]);
+ covariancePositionEstimationK[2][1]=covariancePositionEstimationK[2][1] - kalmanGain3X3[1][0]*(kalmanGain3X3[2][0]*compositeInnovationCovariance3x3[0][0] + kalmanGain3X3[2][1]*compositeInnovationCovariance3x3[1][0] + kalmanGain3X3[2][2]*compositeInnovationCovariance3x3[2][0]) - kalmanGain3X3[1][1]*(kalmanGain3X3[2][0]*compositeInnovationCovariance3x3[0][1] + kalmanGain3X3[2][1]*compositeInnovationCovariance3x3[1][1] + kalmanGain3X3[2][2]*compositeInnovationCovariance3x3[2][1]) - kalmanGain3X3[1][2]*(kalmanGain3X3[2][0]*compositeInnovationCovariance3x3[0][2] + kalmanGain3X3[2][1]*compositeInnovationCovariance3x3[1][2] + kalmanGain3X3[2][2]*compositeInnovationCovariance3x3[2][2]);
+ covariancePositionEstimationK[2][2]=covariancePositionEstimationK[2][2] - kalmanGain3X3[2][0]*(kalmanGain3X3[2][0]*compositeInnovationCovariance3x3[0][0] + kalmanGain3X3[2][1]*compositeInnovationCovariance3x3[1][0] + kalmanGain3X3[2][2]*compositeInnovationCovariance3x3[2][0]) - kalmanGain3X3[2][1]*(kalmanGain3X3[2][0]*compositeInnovationCovariance3x3[0][1] + kalmanGain3X3[2][1]*compositeInnovationCovariance3x3[1][1] + kalmanGain3X3[2][2]*compositeInnovationCovariance3x3[2][1]) - kalmanGain3X3[2][2]*(kalmanGain3X3[2][0]*compositeInnovationCovariance3x3[0][2] + kalmanGain3X3[2][1]*compositeInnovationCovariance3x3[1][2] + kalmanGain3X3[2][2]*compositeInnovationCovariance3x3[2][2]);
+
+ break;
+ }
+ //big question, in wich coordinate space are those measurements...
+ //try with world coordinate system
+
+ this->xWorld=xEstimatedKNext;
+ this->yWorld=yEstimatedKNext;
+ this->thetaWorld=thetaWorldEstimatedKNext;
+
+
+ //try with robot one
+ /*
+ X=xEstimatedKNext;
+ Y=yEstimatedKNext;
+ theta=thetaWorldEstimatedKNext;
+ this->xWorld=-Y;
+ this->yWorld=X;
+ if(theta >PI/2)
+ this->thetaWorld=-PI+(theta-PI/2);
+ else
+ this->thetaWorld=theta+PI/2;
+
+
+ this->print_map_with_robot_position();
+ pc.printf("\n\rX= %f",this->xWorld);
+ pc.printf("\n\rY= %f",this->yWorld);
+ pc.printf("\n\rtheta= %f",this->thetaWorld);
+ */
+ //update odometrie X Y theta...
+}
+
+
+