public void Add(robot rob, String path, String trackName,
int starting_index, String TrackName, int trackType,
bool mappingOnly)
{
int starting_index1 = starting_index;
int starting_index2 = starting_index;
//starting_index1 += 42;
//rob.correspondence.LoadCalibration(path + trackName + "\\calibration.txt", ref calibration_offset_x, ref calibration_offset_y);
Name = trackName;
robotPath p;
if (!mappingOnly)
{
p = getPath(rob, path, trackName, "L", starting_index1, TrackName, trackType);
Add(p, false);
}
p = getPath(rob, path, trackName, "M", starting_index2, TrackName, trackType);
Add(p, true);
}
public void update()
{
int no_of_cameras = Convert.ToInt32(txtNoOfCameras.Text);
robot new_rob = new robot(no_of_cameras, robot.MAPPING_DPSLAM);
for (int i = 0; i < rob.head.no_of_stereo_cameras; i++)
{
new_rob.head.calibration[i] = rob.head.calibration[i];
new_rob.head.sensormodel[i] = rob.head.sensormodel[i];
}
rob = new_rob;
rob.Name = txtName.Text;
rob.TotalMass_kg = Convert.ToSingle(txtTotalMass.Text);
rob.SetMappingThreads(Convert.ToInt32(txtNoOfThreads.Text));
rob.BodyWidth_mm = Convert.ToSingle(txtBodyWidth.Text);
rob.BodyLength_mm = Convert.ToSingle(txtBodyLength.Text);
rob.BodyHeight_mm = Convert.ToSingle(txtBodyHeight.Text);
rob.BodyShape = cmbBodyShape.SelectedIndex;
rob.propulsionType = Convert.ToInt32(cmbPropulsion.SelectedIndex);
rob.WheelBase_mm = Convert.ToSingle(txtWheelBase.Text);
rob.WheelBaseForward_mm = Convert.ToSingle(txtWheelBaseForward.Text);
rob.WheelDiameter_mm = Convert.ToSingle(txtWheelDiameter.Text);
rob.WheelPositionFeedbackType = Convert.ToInt32(cmbWheelFeedback.SelectedIndex);
rob.GearRatio = Convert.ToInt32(txtGearRatio.Text);
rob.CountsPerRev = Convert.ToInt32(txtCountsPerRev.Text);
rob.MotorNoLoadSpeedRPM = Convert.ToSingle(txtMotorNoLoadSpeedRPM.Text);
rob.MotorTorqueKgMm = Convert.ToSingle(txtMotorTorque.Text);
for (int i = 0; i < rob.head.no_of_stereo_cameras; i++)
{
rob.head.calibration[i].baseline = Convert.ToSingle(txtCameraBaseline.Text);
rob.head.calibration[i].leftcam.camera_FOV_degrees = Convert.ToSingle(txtCameraFOV.Text);
rob.head.calibration[i].rightcam.camera_FOV_degrees = Convert.ToSingle(txtCameraFOV.Text);
rob.head.calibration[i].positionOrientation.roll = Convert.ToSingle(txtRollAngle.Text) * (float)Math.PI / 180.0f;
}
rob.HeadType = Convert.ToInt32(cmbHeadType.SelectedIndex);
rob.HeadSize_mm = Convert.ToSingle(txtHeadSize.Text);
rob.HeadShape = Convert.ToInt32(cmbHeadShape.SelectedIndex);
rob.head.x = Convert.ToSingle(txtHeadPositionLeft.Text);
rob.head.y = Convert.ToSingle(txtHeadPositionForward.Text);
rob.head.z = Convert.ToSingle(txtHeadHeightFromGround.Text);
rob.head.no_of_stereo_cameras = Convert.ToInt32(txtNoOfCameras.Text);
rob.CameraOrientation = Convert.ToInt32(cmbCameraOrientation.SelectedIndex);
rob.LocalGridCellSize_mm = Convert.ToSingle(txtGridCellDimension.Text);
rob.LocalGridLevels = Convert.ToInt32(txtGridLevels.Text);
rob.LocalGridDimension = (int)(Convert.ToInt32(txtGridWidth.Text) / rob.LocalGridCellSize_mm);
rob.LocalGridDimensionVertical = (int)(Convert.ToInt32(txtGridHeight.Text) / rob.LocalGridCellSize_mm);
rob.LocalGridInterval_mm = Convert.ToSingle(txtGridInterval.Text);
rob.LocalGridMappingRange_mm = Convert.ToSingle(txtMappingRange.Text);
rob.LocalGridLocalisationRadius_mm = Convert.ToSingle(txtLocalGridLocalisationRadius.Text);
rob.SetMotionModelTrialPoses(Convert.ToInt32(txtTrialPoses.Text));
rob.SetMotionModelCullingThreshold(Convert.ToInt32(txtCullingThreshold.Text));
rob.EnableScanMatching = chkEnableScanMatching.Checked;
}
/// <summary>
/// calculate the position of the robots head and cameras for this pose
/// </summary>
/// <param name="rob">robot object</param>
/// <param name="head_location">location of the centre of the head</param>
/// <param name="camera_centre_location">location of the centre of each stereo camera</param>
/// <param name="left_camera_location">location of the left camera within each stereo camera</param>
/// <param name="right_camera_location">location of the right camera within each stereo camera</param>
protected void calculateCameraPositions(
robot rob,
ref pos3D head_location,
ref pos3D[] camera_centre_location,
ref pos3D[] left_camera_location,
ref pos3D[] right_camera_location)
{
// calculate the position of the centre of the head relative to
// the centre of rotation of the robots body
pos3D head_centroid = new pos3D(-(rob.BodyWidth_mm / 2) + rob.head.x,
-(rob.BodyLength_mm / 2) + rob.head.y,
rob.head.z);
// location of the centre of the head on the grid map
// adjusted for the robot pose and the head pan and tilt angle.
// Note that the positions and orientations of individual cameras
// on the head have already been accounted for within stereoModel.createObservation
pos3D head_locn = head_centroid.rotate(rob.head.pan + pan, rob.head.tilt, 0);
head_locn = head_locn.translate(x, y, 0);
head_location.copyFrom(head_locn);
for (int cam = 0; cam < rob.head.no_of_stereo_cameras; cam++)
{
// calculate the position of the centre of the stereo camera
// (baseline centre point)
pos3D camera_centre_locn = new pos3D(rob.head.calibration[cam].positionOrientation.x, rob.head.calibration[cam].positionOrientation.y, rob.head.calibration[cam].positionOrientation.y);
camera_centre_locn = camera_centre_locn.rotate(rob.head.calibration[cam].positionOrientation.pan + rob.head.pan + pan, rob.head.calibration[cam].positionOrientation.tilt, rob.head.calibration[cam].positionOrientation.roll);
camera_centre_location[cam] = camera_centre_locn.translate(head_location.x, head_location.y, head_location.z);
// where are the left and right cameras?
// we need to know this for the origins of the vacancy models
float half_baseline_length = rob.head.calibration[cam].baseline / 2;
pos3D left_camera_locn = new pos3D(-half_baseline_length, 0, 0);
left_camera_locn = left_camera_locn.rotate(rob.head.calibration[cam].positionOrientation.pan + rob.head.pan + pan, rob.head.calibration[cam].positionOrientation.tilt, rob.head.calibration[cam].positionOrientation.roll);
pos3D right_camera_locn = new pos3D(-left_camera_locn.x, -left_camera_locn.y, -left_camera_locn.z);
left_camera_location[cam] = left_camera_locn.translate(camera_centre_location[cam].x, camera_centre_location[cam].y, camera_centre_location[cam].z);
right_camera_location[cam] = right_camera_locn.translate(camera_centre_location[cam].x, camera_centre_location[cam].y, camera_centre_location[cam].z);
right_camera_location[cam].pan = left_camera_location[cam].pan;
}
}
private void test_motion_model(bool closed_loop)
{
robot rob = new robot(1);
int min_x_mm = 0;
int min_y_mm = 0;
int max_x_mm = 1000;
int max_y_mm = 1000;
int step_size = (max_y_mm - min_y_mm) / 15;
int x = (max_x_mm - min_x_mm) / 2;
bool initial = true;
float pan = 0; // (float)Math.PI / 4;
for (int y = min_y_mm; y < max_y_mm; y += step_size)
{
if (closed_loop) surveyPosesDummy(rob);
rob.updateFromKnownPosition(null, x, y, pan);
rob.GetBestMotionModel().Show(img_rays, standard_width, standard_height,
min_x_mm, min_y_mm, max_x_mm, max_y_mm,
initial);
initial = false;
}
}
/*
private void test_head()
{
pos3D robotPosition = new pos3D(0, 0, 0);
pos3D robotOrientation = new pos3D(0, 0, 0);
beginStopWatch();
for (int i = 0; i < view.Length; i++)
{
for (int cam = 0; cam < 4; cam++)
{
//invent some stereo features
for (int f = 0; f < stereo_features.Length; f += 3)
{
stereo_features[f] = rnd.Next(robot_head.image_width - 1);
stereo_features[f + 1] = rnd.Next(robot_head.image_height - 1);
//stereo_features[f] = (robot_head.image_width*1/10) + (rnd.Next(robot_head.image_width/300) - 1);
//stereo_features[f + 1] = rnd.Next(robot_head.image_height - 1);
stereo_features[f + 2] = rnd.Next(robot_head.image_width * 35 / 100);
}
robot_head.setStereoFeatures(cam, stereo_features, stereo_uncertainties, stereo_features.Length);
}
view[i] = stereo_model.createViewpoint(robot_head, robotOrientation);
view[0].showAbove(img_rays, standard_width, standard_height, 2000, 255, 255, 255, true, 0, false);
robotPosition.y += 0;
robotPosition.pan += 0.0f;
}
long mappingTime = endStopWatch();
txtMappingTime.Text = Convert.ToString(mappingTime);
}
*/
/*
private void test_head2()
{
robot_head = new stereoHead(2);
robot_head.initDualCam();
pos3D robotPosition = new pos3D(0, 0, 0);
pos3D robotOrientation = new pos3D(0, 0, 0);
beginStopWatch();
for (int i = 0; i < view.Length; i++)
{
for (int cam = 0; cam < 2; cam++)
{
//invent some stereo features
for (int f = 0; f < stereo_features.Length; f += 3)
{
stereo_features[f] = rnd.Next(robot_head.image_width - 1);
stereo_features[f + 1] = robot_head.image_height / 2; // rnd.Next(robot_head.image_height - 1);
//stereo_features[f] = (robot_head.image_width*1/10) + (rnd.Next(robot_head.image_width/300) - 1);
//stereo_features[f + 1] = rnd.Next(robot_head.image_height - 1);
stereo_features[f + 2] = rnd.Next(robot_head.image_width * 35 / 100);
}
robot_head.setStereoFeatures(cam, stereo_features, stereo_uncertainties, stereo_features.Length);
}
view[i] = stereo_model.createViewpoint(robot_head, robotOrientation);
view[0].showFront(img_rays, standard_width, standard_height, 2000, 255, 255, 255, true);
robotPosition.y += 0;
robotPosition.pan += 0.0f;
}
long mappingTime = endStopWatch();
txtMappingTime.Text = Convert.ToString(mappingTime);
}
*/
/*
private void test_grid()
{
occupancygridClassic grd = new occupancygridClassic(128, 32);
pos3D robotPosition = new pos3D(0, 0, 0);
pos3D robotOrientation = new pos3D(0, 0, 0);
beginStopWatch();
//int i = 0;
//for (i = 0; i < 9; i++)
{
for (int cam = 0; cam < 4; cam++)
{
//invent some stereo features
for (int f = 0; f < stereo_features.Length; f += 3)
{
stereo_features[f] = rnd.Next(robot_head.image_width - 1);
stereo_features[f + 1] = rnd.Next(robot_head.image_height - 1);
stereo_features[f + 2] = rnd.Next(robot_head.image_width * 35 / 100);
}
robot_head.setStereoFeatures(cam, stereo_features, stereo_uncertainties, stereo_features.Length);
}
view[0] = stereo_model.createViewpoint(robot_head, robotOrientation);
pos3D centre = new pos3D(0, 0, 0);
grd.insert(view[0],true,centre);
//view[0].show(img_rays, standard_width, standard_height, 2000, 255, 255, 255, true);
robotPosition.y += 50;
robotPosition.pan += 0.0f;
}
long mappingTime = endStopWatch();
txtMappingTime.Text = Convert.ToString(mappingTime);
grd.show(img_rays, standard_width, standard_height);
}
*/
/// <summary>
/// generate scores for poses. This is only for testing purposes.
/// </summary>
/// <param name="rob"></param>
private void surveyPosesDummy(robot rob)
{
motionModel motion_model = rob.GetBestMotionModel();
// examine the pose list
for (int sample = 0; sample < motion_model.survey_trial_poses; sample++)
{
particlePath path = (particlePath)motion_model.Poses[sample];
particlePose pose = path.current_pose;
float dx = rob.x - pose.x;
float dy = rob.y - pose.y;
float dist = (float)Math.Sqrt((dx * dx) + (dy * dy));
float score = 1.0f / (1 + dist);
// update the score for this pose
motion_model.updatePoseScore(path, score);
}
// indicate that the pose scores have been updated
motion_model.PosesEvaluated = true;
}
public static void Main(string[] args)
{
// extract command line parameters
ArrayList parameters = commandline.ParseCommandLineParameters(args, "-", GetValidParameters());
string help_str = commandline.GetParameterValue("help", parameters);
if (help_str != "")
{
ShowHelp();
}
else
{
Console.WriteLine("stereosensormodel version 0.1");
int no_of_cameras = 1;
robot rob = new robot(no_of_cameras, robot.MAPPING_DPSLAM);
string filename = commandline.GetParameterValue("filename", parameters);
if (filename == "") filename = "sensormodel.xml";
rob.integer_sensor_model_values = false;
string integer_sensor_model_values_str = commandline.GetParameterValue("integer", parameters);
if (integer_sensor_model_values_str != "")
{
Console.WriteLine("Use integer sensor models");
rob.integer_sensor_model_values = true;
}
float baseline_mm = 107;
string baseline_mm_str = commandline.GetParameterValue("baseline", parameters);
if (baseline_mm_str != "")
{
baseline_mm = Convert.ToSingle(baseline_mm_str);
}
float camera_FOV_degrees = 90;
string camera_FOV_degrees_str = commandline.GetParameterValue("fov", parameters);
if (camera_FOV_degrees_str != "")
{
camera_FOV_degrees = Convert.ToSingle(camera_FOV_degrees_str);
}
float LocalGridCellSize_mm = 40;
string LocalGridCellSize_mm_str = commandline.GetParameterValue("cellsize", parameters);
if (LocalGridCellSize_mm_str != "")
{
LocalGridCellSize_mm = Convert.ToSingle(LocalGridCellSize_mm_str);
}
int image_width = 320;
string image_width_str = commandline.GetParameterValue("imagewidth", parameters);
if (image_width_str != "")
{
image_width = Convert.ToInt32(image_width_str);
}
int image_height = image_width / 2;
for (int i = 0; i < rob.head.no_of_stereo_cameras; i++)
{
rob.head.calibration[i].baseline = baseline_mm;
rob.head.calibration[i].leftcam.camera_FOV_degrees = camera_FOV_degrees;
rob.head.calibration[i].rightcam.camera_FOV_degrees = camera_FOV_degrees;
rob.head.calibration[i].positionOrientation.roll = 0;
rob.head.calibration[i].leftcam.image_width = 640;
rob.head.calibration[i].leftcam.image_height = 480;
}
if (File.Exists(filename))
{
Console.WriteLine("Loading " + filename);
rob.head.sensormodel = new rayModelLookup[no_of_cameras];
rob.head.sensormodel[0] = new rayModelLookup(image_width/2, 4000);
rob.head.sensormodel[0].Load(filename);
}
// create the sensor models
Console.Write("Creating sensor models, please wait...");
rob.inverseSensorModel.createLookupTables(rob.head, (int)LocalGridCellSize_mm);
Console.WriteLine("Done");
string raymodel_image_filename = "ray_model.jpg";
Console.WriteLine("Saving ray model image: " + raymodel_image_filename);
int img_width = 640;
int img_height = 480;
byte[] img = new byte[img_width * img_height *3];
rob.inverseSensorModel.ray_model_to_graph_image(img, img_width, img_height);
Bitmap bmp = new Bitmap(img_width, img_height, System.Drawing.Imaging.PixelFormat.Format24bppRgb);
BitmapArrayConversions.updatebitmap_unsafe(img, bmp);
bmp.Save(raymodel_image_filename, System.Drawing.Imaging.ImageFormat.Jpeg);
string distribution_image_filename = "gaussian_distribution.jpg";
Console.WriteLine("Saving gaussian distribution image: " + distribution_image_filename);
rob.inverseSensorModel.showDistribution(img, img_width, img_height);
BitmapArrayConversions.updatebitmap_unsafe(img, bmp);
bmp.Save(distribution_image_filename, System.Drawing.Imaging.ImageFormat.Jpeg);
Console.WriteLine("Saving " + filename);
rob.Save(filename);
}
}
public motionModel(robot rob,
occupancygridMultiHypothesis LocalGrid,
int random_seed)
{
// seed the random number generator
rnd = new Random(random_seed); // MersenneTwister(random_seed);
this.rob = rob;
this.LocalGrid = LocalGrid;
Poses = new List<particlePath>();
ActivePoses = new List<particlePath>();
motion_noise = new float[6];
// some default noise values
int i = 0;
while (i < 2)
{
motion_noise[i] = default_motion_noise_1;
i++;
}
while (i < 4)
{
motion_noise[i] = default_motion_noise_2;
i++;
}
while (i < motion_noise.Length)
{
motion_noise[i] = default_motion_noise_3;
i++;
}
// create some initial poses
createNewPoses(rob.x, rob.y, rob.pan);
}
/// <summary>
/// add an observation taken from this pose
/// </summary>
/// <param name="stereo_rays">list of ray objects in this observation</param>
/// <param name="rob">robot object</param>
/// <param name="LocalGrid">occupancy grid into which to insert the observation</param>
/// <param name="localiseOnly">if true does not add any mapping particles (pure localisation)</param>
/// <returns>localisation matching score</returns>
public float AddObservation(List<evidenceRay>[] stereo_rays,
robot rob,
occupancygridMultiHypothesis LocalGrid,
bool localiseOnly)
{
// clear the localisation score
float localisation_score = occupancygridCellMultiHypothesis.NO_OCCUPANCY_EVIDENCE;
// get the positions of the head and cameras for this pose
pos3D head_location = new pos3D(0,0,0);
pos3D[] camera_centre_location = new pos3D[rob.head.no_of_stereo_cameras];
pos3D[] left_camera_location = new pos3D[rob.head.no_of_stereo_cameras];
pos3D[] right_camera_location = new pos3D[rob.head.no_of_stereo_cameras];
calculateCameraPositions(rob, ref head_location,
ref camera_centre_location,
ref left_camera_location,
ref right_camera_location);
// itterate for each stereo camera
int cam = stereo_rays.Length - 1;
while (cam >= 0)
{
// itterate through each ray
int r = stereo_rays[cam].Count - 1;
while (r >= 0)
{
// observed ray. Note that this is in an egocentric
// coordinate frame relative to the head of the robot
evidenceRay ray = stereo_rays[cam][r];
// translate and rotate this ray appropriately for the pose
evidenceRay trial_ray = ray.trialPose(camera_centre_location[cam].pan,
camera_centre_location[cam].x,
camera_centre_location[cam].y);
// update the grid cells for this ray and update the
// localisation score accordingly
float score =
LocalGrid.Insert(trial_ray, this,
rob.head.sensormodel[cam],
left_camera_location[cam],
right_camera_location[cam],
localiseOnly);
if (score != occupancygridCellMultiHypothesis.NO_OCCUPANCY_EVIDENCE)
if (localisation_score != occupancygridCellMultiHypothesis.NO_OCCUPANCY_EVIDENCE)
localisation_score += score;
else
localisation_score = score;
r--;
}
cam--;
}
return (localisation_score);
}
/// <summary>
/// Show a diagram of the robot in this pose
/// This is useful for checking that the positions of cameras have
/// been calculated correctly
/// </summary>
/// <param name="robot">robot object</param>
/// <param name="img">image as a byte array</param>
/// <param name="width">width of the image</param>
/// <param name="height">height of the image</param>
/// <param name="clearBackground">clear the background before drawing</param>
/// <param name="min_x_mm">top left x coordinate</param>
/// <param name="min_y_mm">top left y coordinate</param>
/// <param name="max_x_mm">bottom right x coordinate</param>
/// <param name="max_y_mm">bottom right y coordinate</param>
/// <param name="showFieldOfView">whether to show the field of view of each camera</param>
public void Show(robot rob,
byte[] img, int width, int height, bool clearBackground,
int min_x_mm, int min_y_mm,
int max_x_mm, int max_y_mm, int line_width,
bool showFieldOfView)
{
if (clearBackground)
for (int i = 0; i < width * height * 3; i++)
img[i] = 255;
// get the positions of the head and cameras for this pose
pos3D head_location = new pos3D(0, 0, 0);
pos3D[] camera_centre_location = new pos3D[rob.head.no_of_stereo_cameras];
pos3D[] left_camera_location = new pos3D[rob.head.no_of_stereo_cameras];
pos3D[] right_camera_location = new pos3D[rob.head.no_of_stereo_cameras];
calculateCameraPositions(rob, ref head_location,
ref camera_centre_location,
ref left_camera_location,
ref right_camera_location);
int w = max_x_mm - min_x_mm;
int h = max_y_mm - min_y_mm;
// draw the body
int xx = (int)((x - min_x_mm) * width / w);
int yy = (int)((y - min_y_mm) * height / h);
int wdth = (int)(rob.BodyWidth_mm * width / w);
int hght = (int)(rob.BodyLength_mm * height / h);
drawing.drawBox(img, width, height, xx, yy, wdth, hght, pan, 0, 255, 0, line_width);
// draw the head
xx = (int)((head_location.x - min_x_mm) * width / w);
yy = (int)((head_location.y - min_y_mm) * height / h);
int radius = (int)(rob.HeadSize_mm * width / w);
drawing.drawBox(img, width, height, xx, yy, radius, radius, head_location.pan, 0, 255, 0, line_width);
// draw the cameras
for (int cam = 0; cam < rob.head.no_of_stereo_cameras; cam++)
{
// draw the left camera
int xx1 = (int)((left_camera_location[cam].x - min_x_mm) * width / w);
int yy1 = (int)((left_camera_location[cam].y - min_y_mm) * height / h);
wdth = (int)((rob.head.calibration[cam].baseline / 4) * width / w);
hght = (int)((rob.head.calibration[cam].baseline / 12) * height / h);
if (hght < 1) hght = 1;
drawing.drawBox(img, width, height, xx1, yy1, wdth, hght, left_camera_location[cam].pan + (float)(Math.PI / 2), 0, 255, 0, line_width);
// draw the right camera
int xx2 = (int)((right_camera_location[cam].x - min_x_mm) * width / w);
int yy2 = (int)((right_camera_location[cam].y - min_y_mm) * height / h);
drawing.drawBox(img, width, height, xx2, yy2, wdth, hght, right_camera_location[cam].pan + (float)(Math.PI / 2), 0, 255, 0, line_width);
if (showFieldOfView)
{
float half_FOV = rob.head.calibration[cam].leftcam.camera_FOV_degrees * (float)Math.PI / 360.0f;
int xx_ray = xx1 + (int)(width * Math.Sin(left_camera_location[cam].pan + half_FOV));
int yy_ray = yy1 + (int)(width * Math.Cos(left_camera_location[cam].pan + half_FOV));
drawing.drawLine(img, width, height, xx1, yy1, xx_ray, yy_ray, 200, 200, 255, 0, false);
xx_ray = xx1 + (int)(width * Math.Sin(left_camera_location[cam].pan - half_FOV));
yy_ray = yy1 + (int)(width * Math.Cos(left_camera_location[cam].pan - half_FOV));
drawing.drawLine(img, width, height, xx1, yy1, xx_ray, yy_ray, 200, 200, 255, 0, false);
xx_ray = xx2 + (int)(width * Math.Sin(right_camera_location[cam].pan + half_FOV));
yy_ray = yy2 + (int)(width * Math.Cos(right_camera_location[cam].pan + half_FOV));
drawing.drawLine(img, width, height, xx2, yy2, xx_ray, yy_ray, 200, 200, 255, 0, false);
xx_ray = xx2 + (int)(width * Math.Sin(right_camera_location[cam].pan - half_FOV));
yy_ray = yy2 + (int)(width * Math.Cos(right_camera_location[cam].pan - half_FOV));
drawing.drawLine(img, width, height, xx2, yy2, xx_ray, yy_ray, 200, 200, 255, 0, false);
}
}
}
/// <summary>
/// reset the simulation
/// Note that the path or pathSegment data is not reset
/// </summary>
public void Reset()
{
// create the robot object
rob = new robot();
// load the design file
rob.Load(RobotDesignFile);
current_time_step = 0;
position_error_mm = 0;
updatePath();
}
public float loadGlimpseSentience(robot rob, String path, String TrackName, String track, int distance_index, int pathPoints, String index)
{
float matching_score = 0;
Byte[] left_bmp = null;
Byte[] right_bmp = null;
String image_filename;
bool mapping = true;
if (index != "M") mapping = false;
int stereo_cam_index = 0;
bool left_camera = true;
for (int i = 0; i < rob.head.no_of_cameras * 2; i++)
{
if (left_camera)
{
image_filename = path + TrackName + "_left_" + Convert.ToString(distance_index + (stereo_cam_index * pathPoints)) + ".bmp";
if (!File.Exists(image_filename)) errorMessage = image_filename + " not found";
rob.head.imageFilename[i] = image_filename;
left_bmp = util.loadFromBitmap(image_filename, rob.head.image_width, rob.head.image_height, 3);
}
else
{
image_filename = path + TrackName + "_right_" + Convert.ToString(distance_index + (stereo_cam_index * pathPoints)) + ".bmp";
if (!File.Exists(image_filename)) errorMessage = image_filename + " not found";
rob.head.imageFilename[i] = image_filename;
right_bmp = util.loadFromBitmap(image_filename, rob.head.image_width, rob.head.image_height, 3);
matching_score += rob.loadRectifiedImages(stereo_cam_index, left_bmp, right_bmp, 3, mapping);
// store images and features for later display
if (stereo_cam_index == 0)
{
image_filenames_stereoCamera0.Add(rob.head.imageFilename[i - 1]);
image_filenames_stereoCamera0.Add(rob.head.imageFilename[i]);
features_stereoCamera0.Add(rob.head.features[stereo_cam_index]);
}
else
{
image_filenames_stereoCamera1.Add(rob.head.imageFilename[i - 1]);
image_filenames_stereoCamera1.Add(rob.head.imageFilename[i]);
features_stereoCamera1.Add(rob.head.features[stereo_cam_index]);
}
stereo_cam_index++;
}
left_camera = !left_camera;
}
return (matching_score);
}
private robotPath getPath(robot rob, String path, String track, String index, int starting_index, String TrackName, int trackType)
{
robotPath rpath = new robotPath();
robotOdometry odometry = new robotOdometry();
odometry.readPathFileSentience(path + track + "\\" + TrackName + ".path", index, rob);
switch (trackType)
{
case 1:
{
// mapping X track
standardXTrack(2000, 500, odometry, index);
break;
}
case 2:
{
//localisation X track
standardXTrack(2000, -500, odometry, index);
break;
}
case 3:
{
//there and back track
odometry.Clear();
thereAndBack(100, 46, odometry, 110, 0, 0);
break;
}
case 4:
{
//square
odometry.Clear();
squareAndBack(100, 10, 6, odometry, 110);
break;
}
case 5:
{
//special
odometry.Clear();
specialTrack(100, 16, 21, 3, odometry, 110);
break;
}
}
if (odometry.no_of_measurements == 0)
{
errorMessage = path + track + "\\" + TrackName + ".path not found or contains no data. ";
errorMessage += "Check that the path file is included as 'Content' within the project folder";
}
for (int distance_index = 0; distance_index < odometry.no_of_measurements; distance_index++)
{
pos3D pos = odometry.getPosition(distance_index);
rob.x = pos.x;
rob.y = pos.y;
rob.z = pos.z;
rob.pan = pos.pan;
rob.tilt = pos.tilt;
rob.roll = pos.roll;
loadGlimpseSentience(rob, path + track + "\\", TrackName, index, distance_index + starting_index, odometry.no_of_measurements, index);
rob.updatePath(rpath);
}
return (rpath);
}
public void testLocalisation(robot rob,
int localisation_track_index,
int localisation_test_index,
occupancygridMultiResolution grid,
int ray_thickness,
int no_of_trial_poses,
bool pruneSurvey,
int survey_diameter_mm,
int randomSeed, int pruneThreshold, float survey_angular_offset,
float momentum,
ref float error_x, ref float error_y, ref float error_pan,
pos3D estimatedPos)
{
robotPath pathLocalisation = getLocalisationTrack(localisation_track_index);
robotPath pathMap = getMappingTrack(localisation_track_index);
viewpoint view_localisation = pathLocalisation.getViewpoint(localisation_test_index);
viewpoint view_map = pathMap.getViewpoint(localisation_test_index);
float max_score = 0;
// position estimate from odometry, which positions the robot within the grid
// as an initial estimate from which to search
pos3D local_odometry_position = view_map.odometry_position.subtract(pathMap.pathCentre());
ArrayList survey_results = rob.sensorModelLocalisation.surveyXYP(view_localisation, grid, survey_diameter_mm, survey_diameter_mm,
no_of_trial_poses, ray_thickness, pruneSurvey, randomSeed,
pruneThreshold, survey_angular_offset,
local_odometry_position, momentum,
ref max_score);
float peak_x = 0;
float peak_y = 0;
float peak_pan = 0;
rob.sensorModelLocalisation.SurveyPeak(survey_results, ref peak_x, ref peak_y);
//float[] peak = rob.sensorModel.surveyPan(view_map, view_localisation, separation_tollerance, ray_thickness, peak_x, peak_y);
float[] peak = rob.sensorModelLocalisation.surveyPan(view_localisation, grid, ray_thickness, peak_x, peak_y);
peak_pan = rob.sensorModelLocalisation.SurveyPeakPan(peak);
float half_track_length = 1000;
float dx = view_localisation.odometry_position.x - view_map.odometry_position.x;
float dy = view_localisation.odometry_position.y - (view_map.odometry_position.y - half_track_length);
float dp = view_localisation.odometry_position.pan - view_map.odometry_position.pan;
error_x = dx + peak_x;
error_y = dy + peak_y;
error_pan = dp + peak_pan;
error_pan = error_pan / (float)Math.PI * 180;
estimatedPos.x = view_map.odometry_position.x - peak_x;
estimatedPos.y = view_map.odometry_position.y - peak_y;
estimatedPos.pan = view_map.odometry_position.pan - peak_pan;
}