private void BuildHistogram()
{
if (scan.Points.Count != 361)
{
Console.WriteLine("Scan count incorrect. It is " + scan.Points.Count);
return;
}
for (int i = 0; i < 361; i++)
{
histogram[i] = 0;
}
for (int i = 0; i < 361; i++)
{
ILidar2DPoint p = scan.Points.ElementAt(i);
if (i - 2 >= 0)
{
histogram[i - 2] += 0.25 * 80 / p.RThetaPoint.R;
}
if (i - 1 >= 0)
{
histogram[i - 1] += 0.5 * 80 / p.RThetaPoint.R;
}
histogram[i] += 80 / p.RThetaPoint.R;
if (i + 1 < 361)
{
histogram[i + 1] += 0.5 * 80 / p.RThetaPoint.R;
}
if (i + 2 < 361)
{
histogram[i + 2] += 0.5 * 80 / p.RThetaPoint.R;
}
}
Console.Clear();
for (int i = 0; i < 361; i += 4)
{
Console.Write((int)histogram[i] + " ");
}
Console.WriteLine("");
}
public void Draw(Renderer r)
{
if (options.Show == false)
{
return;
}
if (scan == null)
{
return; //nothing to do
}
GLUtility.DisableNiceLines();
GLUtility.GoToSensorPose(laserToBody);
lock (this.drawLock)
{
//foreach (ILidar2DPoint sp in scan.Points)
for (int i = startIdx; i <= endIdx; i++)
{
PointF p = PointF.Empty;
ILidar2DPoint sp = scan.Points[i];
if (options.IsUpsideDown)
{
p = new PointF((float)(sp.RThetaPoint.R * Math.Cos(-sp.RThetaPoint.theta + robotPose.yaw) + robotPose.x), (float)(sp.RThetaPoint.R * Math.Sin(-sp.RThetaPoint.theta + robotPose.yaw) + robotPose.y));
}
else
{
p = new PointF((float)(sp.RThetaPoint.R * Math.Cos(sp.RThetaPoint.theta + robotPose.yaw) + robotPose.x), (float)(sp.RThetaPoint.R * Math.Sin(sp.RThetaPoint.theta + robotPose.yaw) + robotPose.y));
}
GLUtility.DrawCross(new GLPen(options.RenderColor, 1), Vector2.FromPointF(p), .1f);
if (options.ShowIndex)
{
GLUtility.DrawString("Index: " + i, Color.Black, p);
}
}
}
if (options.ShowTS)
{
GLUtility.DrawString("Time: " + scan.Timestamp.ToString(), Color.Black, new PointF(0, 0));
}
if (options.ShowOrigin)
{
GLUtility.DrawCircle(new GLPen(Color.Red, 1), new PointF(0, 0), .075f);
}
if (options.ShowBoundary)
{
PointF p = PointF.Empty, p2 = PointF.Empty;
PointF pose = PointF.Empty;
ILidar2DPoint spInitial = scan.Points[0];
ILidar2DPoint spEnd = scan.Points[scan.Points.Count - 1];
if (options.IsUpsideDown)
{
p = new PointF((float)(spInitial.RThetaPoint.R * Math.Cos(-spInitial.RThetaPoint.theta + robotPose.yaw) + robotPose.x), (float)(spInitial.RThetaPoint.R * Math.Sin(-spInitial.RThetaPoint.theta + robotPose.yaw) + robotPose.y));
p2 = new PointF((float)(spEnd.RThetaPoint.R * Math.Cos(-spEnd.RThetaPoint.theta + robotPose.yaw) + robotPose.x), (float)(spEnd.RThetaPoint.R * Math.Sin(-spEnd.RThetaPoint.theta + robotPose.yaw) + robotPose.y));
}
else
{
p = new PointF((float)(spInitial.RThetaPoint.R * Math.Cos(spInitial.RThetaPoint.theta + robotPose.yaw) + robotPose.x), (float)(spInitial.RThetaPoint.R * Math.Sin(spInitial.RThetaPoint.theta + robotPose.yaw) + robotPose.y));
p2 = new PointF((float)(spEnd.RThetaPoint.R * Math.Cos(spEnd.RThetaPoint.theta + robotPose.yaw) + robotPose.x), (float)(spEnd.RThetaPoint.R * Math.Sin(spEnd.RThetaPoint.theta + robotPose.yaw) + robotPose.y));
}
pose.X = (float)robotPose.x; pose.Y = (float)robotPose.y;
GLUtility.DrawLine(new GLPen(options.BoundaryColor, options.BoundaryWidth), p, pose);
GLUtility.DrawLine(new GLPen(options.BoundaryColor, options.BoundaryWidth), p2, pose);
}
GLUtility.ComeBackFromSensorPose();
GLUtility.EnableNiceLines();
}
/// <summary>
/// Update tracker with given input. It will do simple data association with given data (comparing distance between existing targets).
/// </summary>
/// <param name="uPixel">x-pixel in a camera coordinate</param>
/// <param name="vPixel">y-pixel in a camera coordinate</param>
/// <param name="range">laser range reading</param>
/// <param name="currentPose"></param>
/// <returns>target index = targetID</returns>
public int Update(double uPixel, double vPixel, RobotPose currentPose, SensorPose lidarPose, TargetTypes type, ILidar2DPoint lidarPt, string cameraType, int numCamera)
{
Matrix zSCR, Xx2;
double distance = 0;
int targetIdx = 0;
lock (locker)
{
// Compute X and Y position of the target based on the passed lidar point
//Vector2 xyPos = TargetTrackingImpl.FindPosCoord(screenSize, range, uPixel, vPixel, currentPose, null);
// this X Y coordinate = E N
double yaw = currentPose.yaw - Math.PI / 2;
double pitch = currentPose.pitch; double roll = currentPose.roll;
Matrix R_ENU2R = new Matrix(Math.Cos(yaw), Math.Sin(yaw), 0, -Math.Sin(yaw), Math.Cos(yaw), 0, 0, 0, 1) *
new Matrix(1, 0, 0, 0, Math.Cos(pitch), -Math.Sin(pitch), 0, Math.Sin(pitch), Math.Cos(pitch)) *
new Matrix(Math.Cos(roll), 0, Math.Sin(roll), 0, 1, 0, -Math.Sin(roll), 0, Math.Cos(roll));
Matrix localPt = new Matrix(3, 1); localPt[0, 0] = -lidarPt.RThetaPoint.ToVector2().Y - lidarPose.y; localPt[1, 0] = lidarPt.RThetaPoint.ToVector2().X + lidarPose.x;
Matrix globalPt = R_ENU2R.Inverse * localPt;
Vector2 xyPos = new Vector2(globalPt[0, 0] + currentPose.x, globalPt[1, 0] + currentPose.y);
this.xyPosList.Add(xyPos);
#region debugging - go away
// find the closest target
//if (currentTargetPose.Count == 0)
//{
// distance = double.MaxValue;
// targetIdx = 0;
//}
//else
//{
// targetIdx = FindClosestTarget(xyPos, ref distance, type);
//}
//if (type == TargetTypes.PotentialSOOI || type == TargetTypes.ConfirmedSOOI)
//{
// if (distance > staticDistanceThreshold) // if the distance is larger than the threshold, add as a new target
// {
// if (currentTargetPose.Count == currentTargetPose.Capacity)
// currentTargetPose.RemoveAt(0);
// currentTargetPose.Add(xyPos);
// implList.Add(new TargetTrackingImpl(sigma_f, dT, screenSize, cameraType));
// targetIdx = currentTargetPose.Count - 1;
// }
//}
//else if (type == TargetTypes.PotentialMOOI || type == TargetTypes.ConfirmedMOOI)
//{
// if (distance > dynamicDistanceThreshold) // if the distance is larger than the threshold, add as a new target
// {
// if (currentTargetPose.Count == currentTargetPose.Capacity)
// currentTargetPose.RemoveAt(0);
// currentTargetPose.Add(xyPos);
// implList.Add(new TargetTrackingImpl(sigma_f, dT, screenSize, cameraType));
// targetIdx = currentTargetPose.Count - 1;
// }
//}
#endregion
zSCR = new Matrix(3, 1);
zSCR[0, 0] = uPixel; zSCR[1, 0] = vPixel; zSCR[2, 0] = lidarPt.RThetaPoint.R;
Xx2 = new Matrix(9, 1);
Xx2[0, 0] = currentPose.x; Xx2[1, 0] = currentPose.y; /* Xx2[2, 0] = currentPose.z; */ Xx2[2, 0] = 0;
Xx2[3, 0] = currentPose.roll; Xx2[4, 0] = currentPose.pitch; Xx2[5, 0] = currentPose.yaw;
//Xx2[3, 0] = 0; Xx2[4, 0] = 0; Xx2[5, 0] = currentPose.yaw;
Xx2[6, 0] = 0; Xx2[7, 0] = 0; Xx2[8, 0] = 0;
// modification for 3 cameras
if (numCamera == 3)
{
if (uPixel > 0 && uPixel <= 320)
{
Xx2[6, 0] = 50 * Math.PI / 180;
}
else if (uPixel > 320 && uPixel <= 320 * 2)
{
zSCR[0, 0] = uPixel - 320; zSCR[1, 0] = vPixel;
Xx2[6, 0] = 1.5 * Math.PI / 180;
}
else if (uPixel > 320 * 2)
{
zSCR[0, 0] = uPixel - 320 * 2; zSCR[1, 0] = vPixel;
Xx2[6, 0] = -47 * Math.PI / 180;
}
}
// find the most associated target
Matrix Sxx2 = new Matrix(9, 9);
Sxx2[0, 0] = Math.Sqrt(Math.Abs(currentPose.covariance[0, 0]));
Sxx2[1, 1] = Math.Sqrt(Math.Abs(currentPose.covariance[1, 1]));
Sxx2[2, 2] = Math.Sqrt(Math.Abs(currentPose.covariance[2, 2]));
Sxx2[3, 3] = Math.Sqrt(0.01); // roll
Sxx2[4, 4] = Math.Sqrt(0.01); // pitch
Sxx2[5, 5] = Math.Sqrt(0.03); // yaw
Sxx2[6, 6] = Math.Sqrt(0.01); // pan
Sxx2[7, 7] = Math.Sqrt(0.01); // tilt
Sxx2[8, 8] = Math.Sqrt(0.01); // scan
//targetIdx = FindMostAssociatedTarget(xyPos, type, Xx2, Sxx2, zSCR);
Matrix zSCRForTest = new Matrix(2, 1); zSCRForTest[0, 0] = lidarPt.RThetaPoint.R; zSCRForTest[1, 0] = lidarPt.RThetaPoint.theta;
targetIdx = FindMostAssociatedTarget(xyPos, type, Xx2, Sxx2, zSCRForTest);
if (type == TargetTypes.PotentialSOOI || type == TargetTypes.ConfirmedSOOI)
{
if (targetIdx == -1) // if no good associated target found, then add a new one
{
implList.Add(new TargetTrackingImpl(sigma_f, dT, screenSize, cameraType));
targetIdx = implList.Count - 1;
}
}
else if (type == TargetTypes.PotentialMOOI || type == TargetTypes.ConfirmedMOOI)
{
if (targetIdx == -1)
{
implList.Add(new TargetTrackingImpl(sigma_f, dT, screenSize, cameraType));
targetIdx = implList.Count - 1;
}
}
Matrix xhatPOI = new Matrix(7, 1); xhatPOI.Zero();
xhatPOI[0, 0] = xyPos.X; xhatPOI[1, 0] = xyPos.Y; xhatPOI[2, 0] = 0;
if (!implList[targetIdx].IsInitialized)
{
implList[targetIdx].SetInitialPOIInfo(xhatPOI);
}
}
Matrix Sx2 = new Matrix(9, 9);
Sx2[0, 0] = Math.Sqrt(Math.Abs(currentPose.covariance[0, 0]));
Sx2[1, 1] = Math.Sqrt(Math.Abs(currentPose.covariance[1, 1]));
Sx2[2, 2] = Math.Sqrt(Math.Abs(currentPose.covariance[2, 2]));
//Sx2[0, 0] = Math.Sqrt(0.1);
//Sx2[1, 1] = Math.Sqrt(0.1);
//Sx2[2, 2] = Math.Sqrt(0.01);
Sx2[3, 3] = Math.Sqrt(0.01); // roll
Sx2[4, 4] = Math.Sqrt(0.01); // pitch
Sx2[5, 5] = Math.Sqrt(0.01); // yaw
Sx2[6, 6] = Math.Sqrt(0.01); // pan
Sx2[7, 7] = Math.Sqrt(0.01); // tilt
Sx2[8, 8] = Math.Sqrt(0.01); // scan
// update with correct target
implList[targetIdx].UpdateZSCR(zSCR);
implList[targetIdx].UpdateVehicleState(Xx2, currentPose.timestamp);
implList[targetIdx].UpdateSx2(Sx2);
if (implList[targetIdx].Type != TargetTypes.ConfirmedSOOI && implList[targetIdx].Type != TargetTypes.ConfirmedMOOI)
{
implList[targetIdx].SetTargetType(type);
}
implList[targetIdx].Update();
return(targetIdx);
}
static public double FindTargetDistance(ILidarScan <ILidar2DPoint> lidarScan, double u, double v, Dictionary <int, int> colorPix, Vector2 TLCorner, Vector2 RBCorner,
string cameraSize, string camType, RobotPose camPose, TargetTypes type, out ILidar2DPoint lidarPt, ref List <Vector2> ptInBox)
{
#region camera stuff
Matrix DCM4D = new Matrix(4, 4, 1.0);
double[] fc = new double[2];
double[] cc = new double[2];
if (cameraSize.Equals("320x240"))
{
//for 320 x 240 image with Unibrain Fire-i camera
if (camType.Equals("Fire-i"))
{
fc[0] = 384.4507; fc[1] = 384.1266;
cc[0] = 155.1999; cc[1] = 101.5641;
}
// Fire-Fly MV
else if (camType.Equals("FireFly"))
{
fc[0] = 345.26498; fc[1] = 344.99438;
cc[0] = 159.36854; cc[1] = 118.26944;
}
}
else if (cameraSize.Equals("640x480"))
{
// for 640 x 480 image with Unibrain Fire-i camera
if (camType.Equals("Fire-i"))
{
fc[0] = 763.5805; fc[1] = 763.8337;
cc[0] = 303.0963; cc[1] = 215.9287;
}
// for Fire-Fly MV (Point Gray)
else if (camType.Equals("FireFly"))
{
fc[0] = 691.09778; fc[1] = 690.70187;
cc[0] = 324.07388; cc[1] = 234.22204;
}
}
double alpha_c = 0;
// camera matrix
Matrix KK = new Matrix(fc[0], alpha_c * fc[0], cc[0], 0, fc[1], cc[1], 0, 0, 1);
#endregion
// update DCM for point transformation
DCM4D[0, 3] = camPose.x; DCM4D[1, 3] = camPose.y; DCM4D[2, 3] = camPose.z;
DCM4D[0, 0] = Math.Cos(camPose.yaw); DCM4D[1, 1] = Math.Cos(camPose.yaw);
DCM4D[0, 1] = Math.Sin(camPose.yaw); DCM4D[1, 0] = -Math.Sin(camPose.yaw);
List <Vector2> pixelList = new List <Vector2>(lidarScan.Points.Count);
List <ILidar2DPoint> lidarScanInBox = new List <ILidar2DPoint>();
foreach (ILidar2DPoint pt in lidarScan.Points)
{
Matrix point = new Matrix(4, 1);
point[0, 0] = -pt.RThetaPoint.ToVector4().Y;
point[1, 0] = pt.RThetaPoint.ToVector4().X;
point[2, 0] = pt.RThetaPoint.ToVector4().Z;
point[3, 0] = 1;
Matrix transPt = DCM4D * point;
Matrix ptImgPlane = new Matrix(3, 1);
ptImgPlane[0, 0] = transPt[0, 0] / transPt[1, 0];
ptImgPlane[1, 0] = -transPt[2, 0] / transPt[1, 0];
ptImgPlane[2, 0] = transPt[1, 0] / transPt[1, 0];
ptImgPlane = KK * ptImgPlane;
pixelList.Add(new Vector2(ptImgPlane[0, 0], ptImgPlane[1, 0]));
if (ptImgPlane[0, 0] >= TLCorner.X && ptImgPlane[0, 0] <= RBCorner.X && ptImgPlane[1, 0] >= TLCorner.Y && ptImgPlane[1, 0] <= RBCorner.Y)
{
if (colorPix.Count > 0)
{
if (colorPix.ContainsKey((int)ptImgPlane[0, 0]) && colorPix[(int)ptImgPlane[0, 0]] == 255)
{
lidarScanInBox.Add(pt);
ptInBox.Add(new Vector2(ptImgPlane[0, 0], ptImgPlane[1, 0]));
}
}
else
{
lidarScanInBox.Add(pt);
ptInBox.Add(new Vector2(ptImgPlane[0, 0], ptImgPlane[1, 0]));
}
}
}
if (lidarScanInBox.Count == 0)
{
lidarPt = null;
return(-1);
}
lidarPt = FineTargetDistanceClusterBased(lidarScanInBox);
if (lidarPt == null)
{
return(-1);
}
return(lidarPt.RThetaPoint.R);
}
/// <summary>
/// Update OccupancyGrid based on lidarScan and robotPose received
/// </summary>
/// <param name="lidarScan"></param>
/// <param name="currentRobotPose"></param>
public void UpdateOccupancyGrid(ILidarScan <ILidar2DPoint> lidarScan, int robotID, int scannerID, PoseFilterState currentRobotPose, SensorPose lidarPose, List <Polygon> dynamicObstacles)
{
if (robotID == 1)
{
MAXRANGESick = 7.0;
}
else if (robotID == 3)
{
MAXRANGESick = 30.0;
}
if (lidarPose == null)
{
lidarPose = new SensorPose(0, 0, 0.5, 0, 0 * Math.PI / 180.0, 0, 0);
}
if (laser2RobotTransMatrixDictionary.ContainsKey(robotID))
{
if (laser2RobotTransMatrixDictionary[robotID].ContainsKey(scannerID))
{
JTpl = jacobianLaserPoseDictionary[robotID][scannerID];
laserToRobotDCM = laser2RobotTransMatrixDictionary[robotID][scannerID];
}
else
{
Matrix4 laser2RobotDCM = Matrix4.FromPose(lidarPose);
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 4; j++)
{
laserToRobotDCM[i, j] = laser2RobotDCM[i, j];
}
}
laser2RobotTransMatrixDictionary[robotID].Add(scannerID, laserToRobotDCM);
jacobianLaserPoseDictionary[robotID].Add(scannerID, ComputeJacobian(lidarPose.yaw, lidarPose.pitch, lidarPose.roll));
JTpl = jacobianLaserPoseDictionary[robotID][scannerID];
}
}
else
{
laser2RobotTransMatrixDictionary.Add(robotID, new Dictionary <int, UMatrix>());
jacobianLaserPoseDictionary.Add(robotID, new Dictionary <int, UMatrix>());
Matrix4 laser2RobotDCM = Matrix4.FromPose(lidarPose);
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 4; j++)
{
laserToRobotDCM[i, j] = laser2RobotDCM[i, j];
}
}
laser2RobotTransMatrixDictionary[robotID].Add(scannerID, new UMatrix(laserToRobotDCM));
jacobianLaserPoseDictionary[robotID].Add(scannerID, ComputeJacobian(lidarPose.yaw, lidarPose.pitch, lidarPose.roll));
JTpl = jacobianLaserPoseDictionary[robotID][scannerID];
}
// calculate robot2global transformation matrix
if (currentRobotPose == null)
{
return;
}
Matrix4 robot2GlocalDCM = Matrix4.FromPose(currentRobotPose);
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 4; j++)
{
robotToGlocalDCM[i, j] = robot2GlocalDCM[i, j];
}
}
if (lidarScan == null)
{
return;
}
UMatrix JTpr = ComputeJacobianQ(currentRobotPose.q1, currentRobotPose.q2, currentRobotPose.q3, currentRobotPose.q4);
List <UMatrix> JfPrCubixLaserToRobotDCM = new List <UMatrix>(6);
List <UMatrix> RobotToGlocalDCMJfPlCubix = new List <UMatrix>(7);
for (int i = 0; i < 7; i++)
{
//derivative of the robot transform matrtix w.r.t. some element of the robot psoe
UMatrix j = new UMatrix(4, 4);
j[0, 0] = JTpr[0, i]; j[1, 0] = JTpr[1, i]; j[2, 0] = JTpr[2, i]; j[3, 0] = JTpr[3, i];
j[0, 1] = JTpr[4, i]; j[1, 1] = JTpr[5, i]; j[2, 1] = JTpr[6, i]; j[3, 1] = JTpr[7, i];
j[0, 2] = JTpr[8, i]; j[1, 2] = JTpr[9, i]; j[2, 2] = JTpr[10, i]; j[3, 2] = JTpr[11, i];
j[0, 3] = JTpr[12, i]; j[1, 3] = JTpr[13, i]; j[2, 3] = JTpr[14, i]; j[3, 3] = JTpr[15, i];
JfPrCubixLaserToRobotDCM.Add(j * laserToRobotDCM);
if (i == 7)
{
continue; // same as break
}
UMatrix tempJacobianPl = new UMatrix(4, 4);
tempJacobianPl[0, 0] = JTpl[0, i]; tempJacobianPl[1, 0] = JTpl[1, i]; tempJacobianPl[2, 0] = JTpl[2, i]; tempJacobianPl[3, 0] = JTpl[3, i];
tempJacobianPl[0, 1] = JTpl[4, i]; tempJacobianPl[1, 1] = JTpl[5, i]; tempJacobianPl[2, 1] = JTpl[6, i]; tempJacobianPl[3, 1] = JTpl[7, i];
tempJacobianPl[0, 2] = JTpl[8, i]; tempJacobianPl[1, 2] = JTpl[9, i]; tempJacobianPl[2, 2] = JTpl[10, i]; tempJacobianPl[3, 2] = JTpl[11, i];
tempJacobianPl[0, 3] = JTpl[12, i]; tempJacobianPl[1, 3] = JTpl[13, i]; tempJacobianPl[2, 3] = JTpl[14, i]; tempJacobianPl[3, 3] = JTpl[15, i];
RobotToGlocalDCMJfPlCubix.Add(robotToGlocalDCM * tempJacobianPl);
}
UMatrix laserToENU = robotToGlocalDCM * laserToRobotDCM;
//UMatrix pijCell = new UMatrix(rangeToApply * 2 + 1, rangeToApply * 2 + 1);
// update covariance
UpdateCovarianceQ(currentRobotPose.Covariance);
//SickPoint p = new SickPoint(new RThetaCoordinate(1.0f, 0.0f));
for (int laserIndex = 0; laserIndex < lidarScan.Points.Count; laserIndex++)
{
lock (locker)
{
ILidar2DPoint p = lidarScan.Points[laserIndex];
if (scannerID == 1)
{
if (p.RThetaPoint.R >= MAXRANGESick || p.RThetaPoint.R <= MINRANGESick)
{
continue;
}
}
else if (scannerID == 2)
{
if (p.RThetaPoint.R >= MAXRANGEHokuyo || p.RThetaPoint.R <= MINRANGEHokuyo || laserIndex < hokuyoStartIdx || laserIndex > hokuyoEndIdx)
{
continue;
}
}
bool hitDynamicObstacles = false;
// figure out if this lidar point is hitting other robot
// find laser points in 3D space
// first define 2D point on the laser plane
UMatrix laserPoint = new UMatrix(4, 1);
double deg = (p.RThetaPoint.theta * 180.0 / Math.PI);
int thetaDegIndex = 0;
if (scannerID == 2) // hokuyo
{
thetaDegIndex = (int)Math.Round((deg + laserHalfAngleHokuyo) * 2.84); // % 360;
}
else if (scannerID == 1) // sick
{
thetaDegIndex = (int)Math.Round((deg + laserHalfAngleSick) * 2) % 360;
}
double cosTheta = 0, sinTheta = 0;
if (scannerID == 1)
{
cosTheta = cosLookupSick[thetaDegIndex];
sinTheta = sinLookupSick[thetaDegIndex];
}
else if (scannerID == 2)
{
cosTheta = cosLookupHokuyo[thetaDegIndex];
sinTheta = sinLookupHokuyo[thetaDegIndex];
}
// initial laser points
laserPoint[0, 0] = p.RThetaPoint.R * cosTheta;
laserPoint[1, 0] = p.RThetaPoint.R * sinTheta;
laserPoint[2, 0] = 0;
laserPoint[3, 0] = 1;
//calculate r_hat_ENU
UMatrix r_hat_ENU = laserToENU * laserPoint;
foreach (Polygon dp in dynamicObstacles)
{
if (dp.IsInside(new Vector2(r_hat_ENU[0, 0], r_hat_ENU[1, 0])))
{
hitDynamicObstacles = true;
break;
}
}
if (hitDynamicObstacles)
{
continue;
}
//-------------------------------//
// COVARIANCE UMatrix CALCULATION //
//-------------------------------//
UMatrix JRr = new UMatrix(4, 2);
JRr.Zero();
JRr[0, 0] = cosTheta;
JRr[0, 1] = -p.RThetaPoint.R * sinTheta;
JRr[1, 0] = sinTheta;
JRr[1, 1] = p.RThetaPoint.R * cosTheta;
UMatrix Jfr = new UMatrix(3, 2); // 3x2
Jfr = (laserToENU * JRr).Submatrix(0, 2, 0, 1); // 4x4 * 4x4 * 4x2
UMatrix Jfpr = new UMatrix(3, 7);
UMatrix Jfpl = new UMatrix(3, 6);
for (int i = 0; i < 7; i++) //for each state var (i.e. x,y,z,y,p,r)
{
UMatrix JfprTemp = (JfPrCubixLaserToRobotDCM[i]) * laserPoint; // 4 by 1 UMatrix
Jfpr[0, i] = JfprTemp[0, 0];
Jfpr[1, i] = JfprTemp[1, 0];
Jfpr[2, i] = JfprTemp[2, 0];
//UMatrix JfplTemp = (RobotToGlocalDCMJfPlCubix[i]) * laserPoint; // 4 by 1 UMatrix
//Jfpl[0, i] = JfplTemp[0, 0];
//Jfpl[1, i] = JfplTemp[1, 0];
//Jfpl[2, i] = JfplTemp[2, 0];
}
UMatrix JfprQprJfprT = new UMatrix(3, 3);
UMatrix JfplQplJfplT = new UMatrix(3, 3);
UMatrix JfrQrJfrT = new UMatrix(3, 3);
JfprQprJfprT = (Jfpr * covRobotPoseQ) * Jfpr.Transpose();
//JfplQplJfplT = (Jfpl * covLaserPose) * Jfpl.Transpose(); // not doing because covariance of laser point is so small
JfrQrJfrT = (Jfr * covLaserScan) * Jfr.Transpose();
// add above variables together and get the covariance
UMatrix covRHatENU = JfprQprJfprT + /*JfplQplJfplT +*/ JfrQrJfrT; // 3x3 UMatrix
//-----------------------------//
// FIND WHICH CELLS TO COMPUTE //
//-----------------------------//
// find out cells around this laser point
int laserPointIndexX = 0;
int laserPointIndexY = 0;
//this is used just to do the transformation from reaal to grid and visa versa
psig_u_hat_square.GetIndicies(r_hat_ENU[0, 0], r_hat_ENU[1, 0], out laserPointIndexX, out laserPointIndexY); // get cell (r_hat_ENU_X, r_hat_ENU_y)
if ((laserPointIndexX < 0 || laserPointIndexX >= numCellX) || (laserPointIndexY < 0 || laserPointIndexY >= numCellY))
{
continue;
}
int rangeToApplyX = (int)Math.Round(Math.Sqrt(covRHatENU[0, 0]) / (pij_sum.ResolutionX * 2)) * 2;
int rangeToApplyY = (int)Math.Round(Math.Sqrt(covRHatENU[1, 1]) / (pij_sum.ResolutionY * 2)) * 2;
//-----------------------------------------//
// COMPUTE THE DISTRIBUTION OF UNCERTAINTY //
//-----------------------------------------//
UMatrix pijCell = new UMatrix(rangeToApplyY * 2 + 1, rangeToApplyX * 2 + 1);
double sigX = Math.Sqrt(covRHatENU[0, 0]);
double sigY = Math.Sqrt(covRHatENU[1, 1]);
double rho = covRHatENU[1, 0] / (sigX * sigY);
double logTerm = Math.Log(2 * Math.PI * sigX * sigY * Math.Sqrt(1 - (rho * rho)));
double xTermDenom = (1 - (rho * rho));
//for (int i = -rangeToApply; i <= rangeToApply; i++) // row
for (int i = -rangeToApplyX; i <= rangeToApplyX; i++) // row
{
//for (int j = -rangeToApplyX; j <= rangeToApplyX; j++) // column
for (int j = -rangeToApplyY; j <= rangeToApplyY; j++) // column
{
if (laserPointIndexX + i < 0 || laserPointIndexX + i >= numCellX || laserPointIndexY + j < 0 || laserPointIndexY + j >= numCellY)
{
continue;
}
// estimate using Bivariate Normal Distribution
double posX = 0; double posY = 0;
psig_u_hat_square.GetReals(laserPointIndexX + i, laserPointIndexY + j, out posX, out posY);
posX += psig_u_hat_square.ResolutionX / 2;
posY += psig_u_hat_square.ResolutionY / 2;
double x = posX - r_hat_ENU[0, 0];
double y = posY - r_hat_ENU[1, 0];
double z = (x * x) / (sigX * sigX) -
(2 * rho * x * y / (sigX * sigY)) +
(y * y) / (sigY * sigY);
double xTerm = -0.5 * z / xTermDenom;
// chi2 test
//if ((2 * (1 - (rho * rho))) * ((x * x) / (sigX * sigX) + (y * y) / (sigY * sigY) - (2 * rho * x * y) / (sigX * sigY)) > 15.2)
// continue;
pijCell[j + rangeToApplyY, i + rangeToApplyX] = Math.Exp(xTerm - logTerm) * psig_u_hat_square.ResolutionX * psig_u_hat_square.ResolutionY;
laserHit.SetCellByIdx(laserPointIndexX + i, laserPointIndexY + j, laserHit.GetCellByIdxUnsafe(laserPointIndexX + i, laserPointIndexY + j) + 1);
}
}
//---------------------------//
// COMPUTE HEIGHT ESTIMATION //
//---------------------------//
UMatrix PEN = covRHatENU.Submatrix(0, 1, 0, 1);
UMatrix PENInv = PEN.Inverse2x2;
UMatrix PuEN = new UMatrix(1, 2);
UMatrix PENu = new UMatrix(2, 1);
UMatrix PuENPENInv = PuEN * PENInv;
UMatrix uHatMatrix = new UMatrix(rangeToApplyY * 2 + 1, rangeToApplyX * 2 + 1);
UMatrix sigUHatMatrix = new UMatrix(rangeToApplyY * 2 + 1, rangeToApplyX * 2 + 1);
PuEN[0, 0] = covRHatENU[2, 0];
PuEN[0, 1] = covRHatENU[2, 1];
PENu[0, 0] = covRHatENU[0, 2];
PENu[1, 0] = covRHatENU[1, 2];
double sig_u_hat_product = (PuENPENInv * PENu)[0, 0]; // output = 1x1 UMatrix
for (int i = -rangeToApplyX; i <= rangeToApplyX; i++) // row
{
for (int j = -rangeToApplyY; j <= rangeToApplyY; j++) // column
{
UMatrix ENmr_EN = new UMatrix(2, 1);
double posX = 0; double posY = 0;
psig_u_hat_square.GetReals(laserPointIndexX + i, laserPointIndexY + j, out posX, out posY);
ENmr_EN[0, 0] = posX - r_hat_ENU[0, 0];
ENmr_EN[1, 0] = posY - r_hat_ENU[1, 0];
double u_hat_product = (PuENPENInv * (ENmr_EN))[0, 0]; // output = 1x1 UMatrix
uHatMatrix[j + rangeToApplyY, i + rangeToApplyX] = r_hat_ENU[2, 0] + u_hat_product;
sigUHatMatrix[j + rangeToApplyY, i + rangeToApplyX] = covRHatENU[2, 2] - sig_u_hat_product;
}
}
//-------------------------------------------//
// ASSIGN FINAL VALUES TO THE OCCUPANCY GRID //
//-------------------------------------------//
for (int i = -rangeToApplyX; i <= rangeToApplyX; i++)
{
for (int j = -rangeToApplyY; j <= rangeToApplyY; j++)
{
int indexXToUpdate = laserPointIndexX + i;
int indexYToUpdate = laserPointIndexY + j;
// if the cell to update is out of range, continue
if (!psig_u_hat_square.CheckValidIdx(indexXToUpdate, indexYToUpdate))
{
continue;
}
pij_sum.SetCellByIdx(indexXToUpdate, indexYToUpdate,
pijCell[j + rangeToApplyY, i + rangeToApplyX] + pij_sum.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate));
pu_hat.SetCellByIdx(indexXToUpdate, indexYToUpdate,
pijCell[j + rangeToApplyY, i + rangeToApplyX] * uHatMatrix[j + rangeToApplyY, i + rangeToApplyX] + pu_hat.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate));
pu_hat_square.SetCellByIdx(indexXToUpdate, indexYToUpdate,
pijCell[j + rangeToApplyY, i + rangeToApplyX] * uHatMatrix[j + rangeToApplyY, i + rangeToApplyX] * uHatMatrix[j + rangeToApply, i + rangeToApply] + pu_hat_square.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate));
psig_u_hat_square.SetCellByIdx(indexXToUpdate, indexYToUpdate,
pijCell[j + rangeToApplyY, i + rangeToApplyX] * sigUHatMatrix[j + rangeToApplyY, i + rangeToApplyX] + psig_u_hat_square.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate));
uhatGM.SetCellByIdx(indexXToUpdate, indexYToUpdate,
(pu_hat.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate) / pij_sum.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate)));
double largeU = (pu_hat.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate) / pij_sum.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate));
double largeSig = (psig_u_hat_square.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate) + pu_hat_square.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate)) / pij_sum.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate) - largeU * largeU;
if (pij_sum.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate) > 1)
{
thresholdedHeightMap.SetCellByIdx(indexXToUpdate, indexYToUpdate, largeU); //pij_sum.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate) / laserHit.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate));
}
uhatGM.SetCellByIdx(indexXToUpdate, indexYToUpdate, largeU);
//sigSqrGM.SetCellByIdx(indexXToUpdate, indexYToUpdate, largeU + 2 * Math.Sqrt(largeSig));
if (indexMap.GetCellByIdxUnsafe(indexXToUpdate, indexYToUpdate) != 1.0)
{
Index index = new Index(indexXToUpdate, indexYToUpdate);
indicesDictionary.Add(index, indicesDictionary.Count);
indexMap.SetCellByIdx(indexXToUpdate, indexYToUpdate, 1.0);
}
}
}
} // end foreach
//Console.WriteLine("1: " + sw1.ElapsedMilliseconds +
// " 2: " + sw2.ElapsedMilliseconds +
// " 3: " + sw3.ElapsedMilliseconds +
// " 4: " + sw4.ElapsedMilliseconds +
// " 5: " + sw5.ElapsedMilliseconds +
// " 6: " + sw6.ElapsedMilliseconds +
// " TOTAL: " + (sw1.ElapsedMilliseconds + sw2.ElapsedMilliseconds + sw3.ElapsedMilliseconds + sw4.ElapsedMilliseconds + sw5.ElapsedMilliseconds + sw6.ElapsedMilliseconds).ToString());
} // end function
}
/// <summary>
/// Update OccupancyGrid based on lidarScan and robotPose received
/// </summary>
/// <param name="lidarScan"></param>
/// <param name="currentRobotPose"></param>
public void UpdateOccupancyGrid(ILidarScan <ILidar2DPoint> lidarScan, int robotID, RobotPose currentRobotPose, SensorPose lidarPose, List <Polygon> dynamicObstacles)
{
if (lidarPose == null)
{
lidarPose = new SensorPose(0, 0, 0.5, 0, 0 * Math.PI / 180.0, 0, 0);
}
if (laser2RobotTransMatrixDictionary.ContainsKey(robotID))
{
JTpl = jacobianLaserPoseDictionary[robotID];
laserToRobotDCM = laser2RobotTransMatrixDictionary[robotID];
}
else
{
Matrix4 laser2RobotDCM = Matrix4.FromPose(lidarPose);
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 4; j++)
{
laserToRobotDCM[i, j] = laser2RobotDCM[i, j];
}
}
laser2RobotTransMatrixDictionary.Add(robotID, laserToRobotDCM);
jacobianLaserPoseDictionary.Add(robotID, ComputeJacobian(lidarPose.yaw, lidarPose.pitch, lidarPose.roll));
JTpl = jacobianLaserPoseDictionary[robotID];
}
// calculate robot2global transformation matrix
Matrix4 robot2GlocalDCM = Matrix4.FromPose(currentRobotPose);
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 4; j++)
{
robotToGlocalDCM[i, j] = robot2GlocalDCM[i, j];
}
}
if (lidarScan == null)
{
return;
}
Stopwatch sw1 = new Stopwatch();
Stopwatch sw2 = new Stopwatch();
Stopwatch sw3 = new Stopwatch();
Stopwatch sw4 = new Stopwatch();
Stopwatch sw5 = new Stopwatch();
Stopwatch sw6 = new Stopwatch();
UMatrix JTpr = ComputeJacobian(currentRobotPose.yaw, currentRobotPose.pitch, currentRobotPose.roll);
List <UMatrix> JfPrCubixLaserToRobotDCM = new List <UMatrix>(6);
List <UMatrix> RobotToGlocalDCMJfPlCubix = new List <UMatrix>(6);
for (int i = 0; i < 6; i++)
{
//derivative of the robot transform matrtix w.r.t. some element of the robot psoe
UMatrix j = new UMatrix(4, 4);
j[0, 0] = JTpr[0, i]; j[1, 0] = JTpr[1, i]; j[2, 0] = JTpr[2, i]; j[3, 0] = JTpr[3, i];
j[0, 1] = JTpr[4, i]; j[1, 1] = JTpr[5, i]; j[2, 1] = JTpr[6, i]; j[3, 1] = JTpr[7, i];
j[0, 2] = JTpr[8, i]; j[1, 2] = JTpr[9, i]; j[2, 2] = JTpr[10, i]; j[3, 2] = JTpr[11, i];
j[0, 3] = JTpr[12, i]; j[1, 3] = JTpr[13, i]; j[2, 3] = JTpr[14, i]; j[3, 3] = JTpr[15, i];
JfPrCubixLaserToRobotDCM.Add(j * laserToRobotDCM);
UMatrix tempJacobianPl = new UMatrix(4, 4);
tempJacobianPl[0, 0] = JTpl[0, i]; tempJacobianPl[1, 0] = JTpl[1, i]; tempJacobianPl[2, 0] = JTpl[2, i]; tempJacobianPl[3, 0] = JTpl[3, i];
tempJacobianPl[0, 1] = JTpl[4, i]; tempJacobianPl[1, 1] = JTpl[5, i]; tempJacobianPl[2, 1] = JTpl[6, i]; tempJacobianPl[3, 1] = JTpl[7, i];
tempJacobianPl[0, 2] = JTpl[8, i]; tempJacobianPl[1, 2] = JTpl[9, i]; tempJacobianPl[2, 2] = JTpl[10, i]; tempJacobianPl[3, 2] = JTpl[11, i];
tempJacobianPl[0, 3] = JTpl[12, i]; tempJacobianPl[1, 3] = JTpl[13, i]; tempJacobianPl[2, 3] = JTpl[14, i]; tempJacobianPl[3, 3] = JTpl[15, i];
RobotToGlocalDCMJfPlCubix.Add(robotToGlocalDCM * tempJacobianPl);
}
UMatrix laserToENU = robotToGlocalDCM * laserToRobotDCM;
UMatrix pijCell = new UMatrix(rangeToApply * 2 + 1, rangeToApply * 2 + 1);
// update covariance
UpdateCovariance(currentRobotPose.covariance);
//SickPoint p = new SickPoint(new RThetaCoordinate(1.0f, 0.0f));
for (int laserIndex = 0; laserIndex < lidarScan.Points.Count; laserIndex++)
{
lock (locker)
{
ILidar2DPoint p = lidarScan.Points[laserIndex];
if (p.RThetaPoint.R >= MAXRANGE)
{
continue;
}
bool hitDynamicObstacles = false;
// figure out if this lidar point is hitting other robot
// find laser points in 3D space
// first define 2D point on the laser plane
UMatrix laserPoint = new UMatrix(4, 1);
double deg = (p.RThetaPoint.theta * 180.0 / Math.PI);
int thetaDegIndex = (int)Math.Round((deg + 90.0) * 2.0) % 360;
double cosTheta = cosLookup[thetaDegIndex];
double sinTheta = sinLookup[thetaDegIndex];
laserPoint[0, 0] = p.RThetaPoint.R * cosTheta;
laserPoint[1, 0] = p.RThetaPoint.R * sinTheta;
laserPoint[2, 0] = 0;
laserPoint[3, 0] = 1;
//calculate r_hat_ENU
UMatrix r_hat_ENU = laserToENU * laserPoint;
foreach (Polygon dp in dynamicObstacles)
{
if (dp.IsInside(new Vector2(r_hat_ENU[0, 0], r_hat_ENU[1, 0])))
{
hitDynamicObstacles = true;
break;
}
}
if (hitDynamicObstacles)
{
continue;
}
//-------------------------------//
// COVARIANCE UMatrix CALCULATION //
//-------------------------------//
UMatrix JRr = new UMatrix(4, 2);
JRr.Zero();
JRr[0, 0] = cosTheta;
JRr[0, 1] = -p.RThetaPoint.R * sinTheta;
JRr[1, 0] = sinTheta;
JRr[1, 1] = p.RThetaPoint.R * cosTheta;
UMatrix Jfr = new UMatrix(3, 2); // 3x2
Jfr = (laserToENU * JRr).Submatrix(0, 2, 0, 1); // 4x4 * 4x4 * 4x2
UMatrix Jfpr = new UMatrix(3, 6);
UMatrix Jfpl = new UMatrix(3, 6);
sw1.Reset();
sw1.Start();
for (int i = 0; i < 6; i++) //for each state var (i.e. x,y,z,y,p,r)
{
UMatrix JfprTemp = (JfPrCubixLaserToRobotDCM[i]) * laserPoint; // 4 by 1 UMatrix
Jfpr[0, i] = JfprTemp[0, 0];
Jfpr[1, i] = JfprTemp[1, 0];
Jfpr[2, i] = JfprTemp[2, 0];
//UMatrix JfplTemp = (RobotToGlocalDCMJfPlCubix[i]) * laserPoint; // 4 by 1 UMatrix
//Jfpl[0, i] = JfplTemp[0, 0];
//Jfpl[1, i] = JfplTemp[1, 0];
//Jfpl[2, i] = JfplTemp[2, 0];
}
sw1.Stop();
sw2.Reset();
sw2.Start();
UMatrix JfprQprJfprT = new UMatrix(3, 3);
UMatrix JfplQplJfplT = new UMatrix(3, 3);
UMatrix JfrQrJfrT = new UMatrix(3, 3);
JfprQprJfprT = (Jfpr * covRobotPose) * Jfpr.Transpose();
//JfplQplJfplT = (Jfpl * covLaserPose) * Jfpl.Transpose();
JfrQrJfrT = (Jfr * covLaserScan) * Jfr.Transpose();
// add above variables together and get the covariance
UMatrix covRHatENU = JfprQprJfprT + /*JfplQplJfplT +*/ JfrQrJfrT; // 3x3 UMatrix
sw2.Stop();
sw3.Reset();
sw3.Start();
//-----------------------------//
// FIND WHICH CELLS TO COMPUTE //
//-----------------------------//
// find out cells around this laser point
int laserPointIndexX = 0;
int laserPointIndexY = 0;
//this is used just to do the transformation from reaal to grid and visa versa
psig_u_hat_square.GetIndicies(r_hat_ENU[0, 0], r_hat_ENU[1, 0], out laserPointIndexX, out laserPointIndexY); // get cell (r_hat_ENU_X, r_hat_ENU_y)
sw3.Stop();
sw4.Reset();
sw4.Start();
//-----------------------------------------//
// COMPUTE THE DISTRIBUTION OF UNCERTAINTY //
//-----------------------------------------//
double sigX = Math.Sqrt(covRHatENU[0, 0]);
double sigY = Math.Sqrt(covRHatENU[1, 1]);
double rho = covRHatENU[1, 0] / (sigX * sigY);
double logTerm = Math.Log(2 * Math.PI * sigX * sigY * Math.Sqrt(1 - (rho * rho)));
double xTermDenom = (1 - (rho * rho));
for (int i = -rangeToApply; i <= rangeToApply; i++) // column
{
for (int j = -rangeToApply; j <= rangeToApply; j++) // row
{
// estimate using Bivariate Normal Distribution
double posX = 0; double posY = 0;
psig_u_hat_square.GetReals(laserPointIndexX + i, laserPointIndexY + j, out posX, out posY);
posX += psig_u_hat_square.ResolutionX / 2;
posY += psig_u_hat_square.ResolutionY / 2;
double x = posX - r_hat_ENU[0, 0];
double y = posY - r_hat_ENU[1, 0];
double z = (x * x) / (sigX * sigX) -
(2 * rho * x * y / (sigX * sigY)) +
(y * y) / (sigY * sigY);
double xTerm = -0.5 * z / xTermDenom;
// chi2 test
//if ((2 * (1 - (rho * rho))) * ((x * x) / (sigX * sigX) + (y * y) / (sigY * sigY) - (2 * rho * x * y) / (sigX * sigY)) > 15.2)
// continue;
pijCell[j + rangeToApply, i + rangeToApply] = Math.Exp(xTerm - logTerm) * psig_u_hat_square.ResolutionX * psig_u_hat_square.ResolutionY;
laserHit.SetCellByIdx(laserPointIndexX + i, laserPointIndexY + j, laserHit.GetCellByIdx(laserPointIndexX + i, laserPointIndexY + j) + 1);
}
}
sw4.Stop();
sw5.Reset();
sw5.Start();
//---------------------------//
// COMPUTE HEIGHT ESTIMATION //
//---------------------------//
// Matrix2 PEN = new Matrix2(covRHatENU[0, 0], covRHatENU[0, 1], covRHatENU[1, 0], covRHatENU[1, 1]);
UMatrix PEN = covRHatENU.Submatrix(0, 1, 0, 1);
UMatrix PENInv = PEN.Inverse2x2;
UMatrix PuEN = new UMatrix(1, 2);
UMatrix PENu = new UMatrix(2, 1);
UMatrix PuENPENInv = PuEN * PENInv;
UMatrix uHatMatrix = new UMatrix(rangeToApply * 2 + 1, rangeToApply * 2 + 1);
UMatrix sigUHatMatrix = new UMatrix(rangeToApply * 2 + 1, rangeToApply * 2 + 1);
PuEN[0, 0] = covRHatENU[2, 0];
PuEN[0, 1] = covRHatENU[2, 1];
PENu[0, 0] = covRHatENU[0, 2];
PENu[1, 0] = covRHatENU[1, 2];
double sig_u_hat_product = (PuENPENInv * PENu)[0, 0]; // output = 1x1 UMatrix
for (int i = -rangeToApply; i <= rangeToApply; i++) // column
{
for (int j = -rangeToApply; j <= rangeToApply; j++) // row
{
UMatrix ENmr_EN = new UMatrix(2, 1);
double posX = 0; double posY = 0;
psig_u_hat_square.GetReals(laserPointIndexX + i, laserPointIndexY + j, out posX, out posY);
ENmr_EN[0, 0] = posX - r_hat_ENU[0, 0];
ENmr_EN[1, 0] = posY - r_hat_ENU[1, 0];
double u_hat_product = (PuENPENInv * (ENmr_EN))[0, 0]; // output = 1x1 UMatrix
uHatMatrix[j + rangeToApply, i + rangeToApply] = r_hat_ENU[2, 0] + u_hat_product;
sigUHatMatrix[j + rangeToApply, i + rangeToApply] = covRHatENU[2, 2] - sig_u_hat_product;
}
}
sw5.Stop();
sw6.Reset();
sw6.Start();
//-------------------------------------------//
// ASSIGN FINAL VALUES TO THE OCCUPANCY GRID //
//-------------------------------------------//
for (int i = -rangeToApply; i <= rangeToApply; i++)
{
for (int j = -rangeToApply; j <= rangeToApply; j++)
{
int indexXToUpdate = laserPointIndexX + i;
int indexYToUpdate = laserPointIndexY + j;
// if the cell to update is out of range, continue
if (!psig_u_hat_square.CheckValidIdx(indexXToUpdate, indexYToUpdate))
{
//Console.WriteLine("Laser points out of the occupancy grid map");
continue;
}
pij_sum.SetCellByIdx(indexXToUpdate, indexYToUpdate,
pijCell[j + rangeToApply, i + rangeToApply] + pij_sum.GetCellByIdx(indexXToUpdate, indexYToUpdate));
pu_hat.SetCellByIdx(indexXToUpdate, indexYToUpdate,
pijCell[j + rangeToApply, i + rangeToApply] * uHatMatrix[j + rangeToApply, i + rangeToApply] + pu_hat.GetCellByIdx(indexXToUpdate, indexYToUpdate));
pu_hat_square.SetCellByIdx(indexXToUpdate, indexYToUpdate,
pijCell[j + rangeToApply, i + rangeToApply] * uHatMatrix[j + rangeToApply, i + rangeToApply] * uHatMatrix[j + rangeToApply, i + rangeToApply] + pu_hat_square.GetCellByIdx(indexXToUpdate, indexYToUpdate));
psig_u_hat_square.SetCellByIdx(indexXToUpdate, indexYToUpdate,
pijCell[j + rangeToApply, i + rangeToApply] * sigUHatMatrix[j + rangeToApply, i + rangeToApply] + psig_u_hat_square.GetCellByIdx(indexXToUpdate, indexYToUpdate));
uhatGM.SetCellByIdx(indexXToUpdate, indexYToUpdate,
(pu_hat.GetCellByIdx(indexXToUpdate, indexYToUpdate) / pij_sum.GetCellByIdx(indexXToUpdate, indexYToUpdate)));
normalisedPijSum.SetCellByIdx(indexXToUpdate, indexYToUpdate, pij_sum.GetCellByIdx(indexXToUpdate, indexYToUpdate) / laserHit.GetCellByIdx(indexXToUpdate, indexYToUpdate));
double largeU = (pu_hat.GetCellByIdx(indexXToUpdate, indexYToUpdate) / pij_sum.GetCellByIdx(indexXToUpdate, indexYToUpdate));
double largeSig = (psig_u_hat_square.GetCellByIdx(indexXToUpdate, indexYToUpdate) + pu_hat_square.GetCellByIdx(indexXToUpdate, indexYToUpdate)) / pij_sum.GetCellByIdx(indexXToUpdate, indexYToUpdate) - largeU * largeU;
uhatGM.SetCellByIdx(indexXToUpdate, indexYToUpdate, largeU);
sigSqrGM.SetCellByIdx(indexXToUpdate, indexYToUpdate, largeSig);
Index index = new Index(indexXToUpdate, indexYToUpdate);
if (!indicesDictionary.ContainsKey(index))
{
indicesDictionary.Add(index, indicesDictionary.Count);
}
/*
* if (indicesDictionary.ContainsKey(index))
* {
* int indexOfIndices = indicesDictionary[index];
* heightList[indexOfIndices] = (float)largeU;
* covList[indexOfIndices] = (float)largeSig;
* pijSumList[indexOfIndices] = (float)pij_sum.GetCellByIdx(indexXToUpdate, indexYToUpdate);
* }
* else
* {
* indicesDictionary.Add(index, indicesDictionary.Count);
* indicesList.Add(new Index(indexXToUpdate, indexYToUpdate));
* heightList.Add((float)largeU);
* covList.Add((float)largeSig);
* pijSumList.Add((float)pij_sum.GetCellByIdx(indexXToUpdate, indexYToUpdate));
* }
*/
}
}
sw6.Stop();
} // end foreach
//Console.WriteLine("1: " + sw1.ElapsedMilliseconds +
// " 2: " + sw2.ElapsedMilliseconds +
// " 3: " + sw3.ElapsedMilliseconds +
// " 4: " + sw4.ElapsedMilliseconds +
// " 5: " + sw5.ElapsedMilliseconds +
// " 6: " + sw6.ElapsedMilliseconds +
// " TOTAL: " + (sw1.ElapsedMilliseconds + sw2.ElapsedMilliseconds + sw3.ElapsedMilliseconds + sw4.ElapsedMilliseconds + sw5.ElapsedMilliseconds + sw6.ElapsedMilliseconds).ToString());
} // end function
}
