/// <summary>
/// any old iron...
/// </summary>
/// <param name="vertical_index">the z position at which to check for garbage</param>
/// <returns>the amount of garbage collected</returns>
public int GarbageCollect(int vertical_index)
{
int collected_items = 0;
if (Hypothesis[vertical_index] != null)
{
int i = Hypothesis[vertical_index].Count - 1;
while ((i >= 0) && (garbage_entries > 0))
{
particleGridCell h = Hypothesis[vertical_index][i];
if (!h.Enabled) // has this hypothesis been marked for deletion?
{
Hypothesis[vertical_index].RemoveAt(i);
garbage_entries--;
collected_items++;
}
i--;
}
// there is no longer any garbage at this vertical index
garbage[vertical_index] = false;
// no hypotheses exist, so remove the list to save on memory usage
if (Hypothesis[vertical_index].Count == 0)
{
Hypothesis[vertical_index] = null;
}
}
return(collected_items);
}
/// <summary>
/// adds a new hypothesis to the map cache
/// </summary>
/// <param name="hypothesis">grid hypothesis to be added</param>
/// <param name="radius_cells">radius of the local map cache</param>
/// <param name="grid_dimension">dimension of the occupancy grid</param>
/// <param name="grid_dimension_vertical">height of the occupancy grid (z axis) in cells</param>
/// <returns>true if the hypothesis was added</returns>
public bool Add(particleGridCell hypothesis,
int radius_cells,
int grid_dimension,
int grid_dimension_vertical)
{
bool added = true;
// create a new list for this grid coordinate if necessary
// allocating memory as its needed for each grid dimension
// is far more efficient than just allocating a big three
// dimensional chunk in one go
if (map_cache == null)
{
// store the top left position of the map cache
map_cache_tx = hypothesis.x - radius_cells;
map_cache_ty = hypothesis.y - radius_cells;
// store the width of the map cache
map_cache_width_cells = radius_cells * 2;
map_cache = new List <particleGridCell> [map_cache_width_cells][][];
}
// get the x,y coordinate within the map cache
int x = hypothesis.x - map_cache_tx;
int y = hypothesis.y - map_cache_ty;
if (((x < 0) || (x >= map_cache_width_cells)) ||
((y < 0) || (y >= map_cache_width_cells)))
{
// we're outside of the cache
added = false;
//resize_map_cache(x, y);
}
else
{
// add the hypothesis to the cache map
int z = hypothesis.z;
// create new lists as they are needed
if (map_cache[x] == null)
{
map_cache[x] = new List <particleGridCell> [map_cache_width_cells][];
}
if (map_cache[x][y] == null)
{
map_cache[x][y] = new List <particleGridCell> [grid_dimension_vertical];
}
if (map_cache[x][y][z] == null)
{
map_cache[x][y][z] = new List <particleGridCell>();
}
// add to the list
map_cache[x][y][z].Add(hypothesis);
}
return(added);
}
/// <summary>
/// distills all grid particles associated with this pose
/// </summary>
/// <param name="grid">grid to be updated</param>
public void Distill(dpslam grid)
{
for (int i = observed_grid_cells.Count - 1; i >= 0; i--)
{
particleGridCell hypothesis = observed_grid_cells[i];
grid.Distill(hypothesis);
}
}
/// <summary>
/// add a new occupancy hypothesis to the list
/// for this grid cell
/// </summary>
/// <param name="h">the hypothesis to be added to this grid cell</param>
public void AddHypothesis(particleGridCell h)
{
int vertical_index = h.z;
if (Hypothesis[vertical_index] == null)
{
Hypothesis[vertical_index] = new List <particleGridCell>();
}
Hypothesis[vertical_index].Add(h);
}
/// <summary>
/// add a new grid hypothesis to this pose
/// </summary>
/// <param name="hypothesis">occupancy hypothesis for a grid cell</param>
/// <param name="radius_cells">local map cache radius in cells</param>
/// <param name="grid_dimension">dimension of the occupancy grid in cells</param>
/// <param name="grid_dimension_vertical">height of the occupancy grid (z axis) in cells</param>
/// <returns>true if the hypothesis was added</returns>
public bool AddHypothesis(
particleGridCell hypothesis,
int radius_cells,
int grid_dimension,
int grid_dimension_vertical)
{
bool added = false;
if (path != null)
{
added = path.Add(hypothesis, radius_cells, grid_dimension, grid_dimension_vertical);
if (added)
{
observed_grid_cells.Add(hypothesis);
}
}
return(added);
}
/// <summary>
/// distill an individual grid particle
/// </summary>
/// <param name="hypothesis">the grid particle to be distilled</param>
public void Distill(particleGridCell hypothesis)
{
int z = hypothesis.z;
// create the distilled array
if (distilled == null)
{
distilled = new particleGridCellBase[Hypothesis.Length];
}
bool initialised = false;
if (distilled[z] == null)
{
// create a new distilled particle
distilled[z] = new particleGridCellBase();
distilled[z].colour = new byte[3];
initialised = true;
}
// update an existing distilled value
distilled[z].probabilityLogOdds += hypothesis.probabilityLogOdds;
// and update the distilled colour value
for (int col = 2; col >= 0; col--)
{
if (initialised)
{
distilled[z].colour[col] = hypothesis.colour[col];
}
else
{
distilled[z].colour[col] = (byte)((hypothesis.colour[col] +
distilled[z].colour[col]) / 2);
}
}
}
/// <summary>
/// inserts the given ray into the grid
/// There are three components to the sensor model used here:
/// two areas determining the probably vacant area and one for
/// the probably occupied space
/// </summary>
/// <param name="ray">ray object to be inserted into the grid</param>
/// <param name="origin">the pose of the robot</param>
/// <param name="sensormodel">the sensor model to be used</param>
/// <param name="leftcam_x">x position of the left camera in millimetres</param>
/// <param name="leftcam_y">y position of the left camera in millimetres</param>
/// <param name="rightcam_x">x position of the right camera in millimetres</param>
/// <param name="rightcam_y">y position of the right camera in millimetres</param>
/// <param name="localiseOnly">if true does not add any mapping particles (pure localisation)</param>
/// <returns>matching probability, expressed as log odds</returns>
public float Insert(
evidenceRay ray,
particlePose origin,
rayModelLookup sensormodel_lookup,
pos3D left_camera_location,
pos3D right_camera_location,
bool localiseOnly)
{
// some constants to aid readability
const int OCCUPIED_SENSORMODEL = 0;
const int VACANT_SENSORMODEL_LEFT_CAMERA = 1;
const int VACANT_SENSORMODEL_RIGHT_CAMERA = 2;
const int X_AXIS = 0;
const int Y_AXIS = 1;
// which disparity index in the lookup table to use
// we multiply by 2 because the lookup is in half pixel steps
float ray_model_interval_pixels = sensormodel_lookup.ray_model_interval_pixels;
int sensormodel_index = (int)Math.Round(ray.disparity / ray_model_interval_pixels);
// the initial models are blank, so just default to the one disparity pixel model
bool small_disparity_value = false;
if (sensormodel_index < 2)
{
sensormodel_index = 2;
small_disparity_value = true;
}
// beyond a certain disparity the ray model for occupied space
// is always only going to be only a single grid cell
if (sensormodel_lookup == null) Console.WriteLine("Sensor models are missing");
if (sensormodel_index >= sensormodel_lookup.probability.GetLength(0))
sensormodel_index = sensormodel_lookup.probability.GetLength(0) - 1;
float xdist_mm=0, ydist_mm=0, zdist_mm=0, xx_mm=0, yy_mm=0, zz_mm=0;
float occupied_dx = 0, occupied_dy = 0, occupied_dz = 0;
float intersect_x = 0, intersect_y = 0, intersect_z = 0;
float centre_prob = 0, prob = 0, prob_localisation = 0; // probability values at the centre axis and outside
float matchingScore = occupancygridCellMultiHypothesis.NO_OCCUPANCY_EVIDENCE; // total localisation matching score
int rayWidth = 0; // widest point in the ray in cells
int widest_point; // widest point index
int step_size = 1;
particleGridCell hypothesis;
// ray width at the fattest point in cells
rayWidth = (int)Math.Round(ray.width / (cellSize_mm * 2));
// calculate the centre position of the grid in millimetres
int half_grid_width_mm = dimension_cells * cellSize_mm / 2;
//int half_grid_width_vertical_mm = dimension_cells_vertical * cellSize_mm / 2;
int grid_centre_x_mm = (int)(x - half_grid_width_mm);
int grid_centre_y_mm = (int)(y - half_grid_width_mm);
int grid_centre_z_mm = (int)z;
//int max_dimension_cells = dimension_cells - rayWidth;
// in turbo mode only use a single vacancy ray
int max_modelcomponent = VACANT_SENSORMODEL_RIGHT_CAMERA;
if (TurboMode) max_modelcomponent = VACANT_SENSORMODEL_LEFT_CAMERA;
float[][] sensormodel_lookup_probability = sensormodel_lookup.probability;
// consider each of the three parts of the sensor model
for (int modelcomponent = OCCUPIED_SENSORMODEL; modelcomponent <= max_modelcomponent; modelcomponent++)
{
// the range from the cameras from which insertion of data begins
// for vacancy rays this will be zero, but will be non-zero for the occupancy area
int starting_range_cells = 0;
switch (modelcomponent)
{
case OCCUPIED_SENSORMODEL:
{
// distance between the beginning and end of the probably
// occupied area
occupied_dx = ray.vertices[1].x - ray.vertices[0].x;
occupied_dy = ray.vertices[1].y - ray.vertices[0].y;
occupied_dz = ray.vertices[1].z - ray.vertices[0].z;
intersect_x = ray.vertices[0].x + (occupied_dx * ray.fattestPoint);
intersect_y = ray.vertices[0].y + (occupied_dy * ray.fattestPoint);
intersect_z = ray.vertices[0].z + (occupied_dz * ray.fattestPoint);
xdist_mm = occupied_dx;
ydist_mm = occupied_dy;
zdist_mm = occupied_dz;
// begin insertion at the beginning of the
// probably occupied area
xx_mm = ray.vertices[0].x;
yy_mm = ray.vertices[0].y;
zz_mm = ray.vertices[0].z;
break;
}
case VACANT_SENSORMODEL_LEFT_CAMERA:
{
// distance between the left camera and the left side of
// the probably occupied area of the sensor model
xdist_mm = intersect_x - left_camera_location.x;
ydist_mm = intersect_y - left_camera_location.y;
zdist_mm = intersect_z - left_camera_location.z;
// begin insertion from the left camera position
xx_mm = left_camera_location.x;
yy_mm = left_camera_location.y;
zz_mm = left_camera_location.z;
step_size = 2;
break;
}
case VACANT_SENSORMODEL_RIGHT_CAMERA:
{
// distance between the right camera and the right side of
// the probably occupied area of the sensor model
xdist_mm = intersect_x - right_camera_location.x;
ydist_mm = intersect_y - right_camera_location.y;
zdist_mm = intersect_z - right_camera_location.z;
// begin insertion from the right camera position
xx_mm = right_camera_location.x;
yy_mm = right_camera_location.y;
zz_mm = right_camera_location.z;
step_size = 2;
break;
}
}
// which is the longest axis ?
int longest_axis = X_AXIS;
float longest = Math.Abs(xdist_mm);
if (Math.Abs(ydist_mm) > longest)
{
// y has the longest length
longest = Math.Abs(ydist_mm);
longest_axis = Y_AXIS;
}
// ensure that the vacancy model does not overlap
// the probably occupied area
// This is crude and could potentially leave a gap
if (modelcomponent != OCCUPIED_SENSORMODEL)
longest -= ray.width;
int steps = (int)(longest / cellSize_mm);
if (steps < 1) steps = 1;
// calculate the range from the cameras to the start of the ray in grid cells
if (modelcomponent == OCCUPIED_SENSORMODEL)
{
if (longest_axis == Y_AXIS)
starting_range_cells = (int)Math.Abs((ray.vertices[0].y - ray.observedFrom.y) / cellSize_mm);
else
starting_range_cells = (int)Math.Abs((ray.vertices[0].x - ray.observedFrom.x) / cellSize_mm);
}
// what is the widest point of the ray in cells
if (modelcomponent == OCCUPIED_SENSORMODEL)
widest_point = (int)(ray.fattestPoint * steps / ray.length);
else
widest_point = steps;
// calculate increment values in millimetres
float x_incr_mm = xdist_mm / steps;
float y_incr_mm = ydist_mm / steps;
float z_incr_mm = zdist_mm / steps;
// step through the ray, one grid cell at a time
int grid_step = 0;
while (grid_step < steps)
{
// is this position inside the maximum mapping range
bool withinMappingRange = true;
if (grid_step + starting_range_cells > max_mapping_range_cells)
{
withinMappingRange = false;
if ((grid_step==0) && (modelcomponent == OCCUPIED_SENSORMODEL))
{
grid_step = steps;
modelcomponent = 9999;
}
}
// calculate the width of the ray in cells at this point
// using a diamond shape ray model
int ray_wdth = 0;
if (rayWidth > 0)
{
if (grid_step < widest_point)
ray_wdth = grid_step * rayWidth / widest_point;
else
{
if (!small_disparity_value)
// most disparity values tail off to some point in the distance
ray_wdth = (steps - grid_step + widest_point) * rayWidth / (steps - widest_point);
else
// for very small disparity values the ray model has an infinite tail
// and maintains its width after the widest point
ray_wdth = rayWidth;
}
}
// localisation rays are wider, to enable a more effective matching score
// which is not too narrowly focussed and brittle
int ray_wdth_localisation = ray_wdth + 1; //localisation_search_cells;
xx_mm += x_incr_mm*step_size;
yy_mm += y_incr_mm*step_size;
zz_mm += z_incr_mm*step_size;
// convert the x millimetre position into a grid cell position
int x_cell = (int)Math.Round((xx_mm - grid_centre_x_mm) / (float)cellSize_mm);
if ((x_cell > ray_wdth_localisation) && (x_cell < dimension_cells - ray_wdth_localisation))
{
// convert the y millimetre position into a grid cell position
int y_cell = (int)Math.Round((yy_mm - grid_centre_y_mm) / (float)cellSize_mm);
if ((y_cell > ray_wdth_localisation) && (y_cell < dimension_cells - ray_wdth_localisation))
{
// convert the z millimetre position into a grid cell position
int z_cell = (int)Math.Round((zz_mm - grid_centre_z_mm) / (float)cellSize_mm);
if ((z_cell >= 0) && (z_cell < dimension_cells_vertical))
{
int x_cell2 = x_cell;
int y_cell2 = y_cell;
// get the probability at this point
// for the central axis of the ray using the inverse sensor model
if (modelcomponent == OCCUPIED_SENSORMODEL)
centre_prob = ray_model_interval_pixels + (sensormodel_lookup_probability[sensormodel_index][grid_step] * ray_model_interval_pixels);
else
// calculate the probability from the vacancy model
centre_prob = vacancyFunction(grid_step / (float)steps, steps);
// width of the localisation ray
for (int width = -ray_wdth_localisation; width <= ray_wdth_localisation; width++)
{
// is the width currently inside the mapping area of the ray ?
bool isInsideMappingRayWidth = false;
if ((width >= -ray_wdth) && (width <= ray_wdth))
isInsideMappingRayWidth = true;
// adjust the x or y cell position depending upon the
// deviation from the main axis of the ray
if (longest_axis == Y_AXIS)
x_cell2 = x_cell + width;
else
y_cell2 = y_cell + width;
// probability at the central axis
prob = centre_prob;
prob_localisation = centre_prob;
// probabilities are symmetrical about the axis of the ray
// this multiplier implements a gaussian distribution around the centre
if (width != 0) // don't bother if this is the centre of the ray
{
// the probability used for wide localisation rays
prob_localisation *= gaussianLookup[Math.Abs(width) * 9 / ray_wdth_localisation];
// the probability used for narrower mapping rays
if (isInsideMappingRayWidth)
prob *= gaussianLookup[Math.Abs(width) * 9 / ray_wdth];
}
if ((cell[x_cell2][y_cell2] != null) && (withinMappingRange))
{
// only localise using occupancy, not vacancy
if (modelcomponent == OCCUPIED_SENSORMODEL)
{
// update the matching score, by combining the probability
// of the grid cell with the probability from the localisation ray
float score = occupancygridCellMultiHypothesis.NO_OCCUPANCY_EVIDENCE;
if (longest_axis == X_AXIS)
score = matchingProbability(x_cell2, y_cell2, z_cell, origin, prob_localisation, ray.colour);
if (longest_axis == Y_AXIS)
score = matchingProbability(x_cell2, y_cell2, z_cell, origin, prob_localisation, ray.colour);
if (score != occupancygridCellMultiHypothesis.NO_OCCUPANCY_EVIDENCE)
{
if (matchingScore != occupancygridCellMultiHypothesis.NO_OCCUPANCY_EVIDENCE)
matchingScore += score;
else
matchingScore = score;
}
}
}
if ((isInsideMappingRayWidth) &&
(withinMappingRange) &&
(!localiseOnly))
{
// add a new hypothesis to this grid coordinate
// note that this is also added to the original pose
hypothesis = new particleGridCell(x_cell2, y_cell2, z_cell,
prob, origin,
ray.colour);
if (origin.AddHypothesis(hypothesis, max_mapping_range_cells, dimension_cells, dimension_cells_vertical))
{
// generate a grid cell if necessary
if (cell[x_cell2][y_cell2] == null)
cell[x_cell2][y_cell2] = new occupancygridCellMultiHypothesis(dimension_cells_vertical);
cell[x_cell2][y_cell2].AddHypothesis(hypothesis);
total_valid_hypotheses++;
}
}
}
}
else grid_step = steps; // its the end of the ray, break out of the loop
}
else grid_step = steps; // its the end of the ray, break out of the loop
}
else grid_step = steps; // time to bail out chaps!
grid_step += step_size;
}
}
return (matchingScore);
}
/// <summary>
/// distill this grid particle
/// </summary>
/// <param name="hypothesis"></param>
public void Distill(
particleGridCell hypothesis)
{
occupancygridCellMultiHypothesis c = cell[hypothesis.x][hypothesis.y];
c.Distill(hypothesis);
Remove(hypothesis);
// occasionally update the navigable space
if (rnd.Next(100) < 5)
updateNavigableSpace(hypothesis.pose, hypothesis.x, hypothesis.y);
}
/// <summary>
/// removes an occupancy hypothesis from a grid cell
/// </summary>
/// <param name="hypothesis">the hypothesis to be removed from the grid</param>
public void Remove(
particleGridCell hypothesis)
{
occupancygridCellMultiHypothesis c = cell[hypothesis.x][hypothesis.y];
// add this to the list of garbage to be collected
if (c.garbage_entries == 0)
garbage.Add(c);
c.garbage[hypothesis.z] = true;
// increment the heap of garbage
c.garbage_entries++;
total_garbage_hypotheses++;
// mark this hypothesis as rubbish
hypothesis.Enabled = false;
total_valid_hypotheses--;
}
/// <summary>
/// distill an individual grid particle
/// </summary>
/// <param name="hypothesis">the grid particle to be distilled</param>
public void Distill(particleGridCell hypothesis)
{
int z = hypothesis.z;
// create the distilled array
if (distilled == null)
distilled = new particleGridCellBase[Hypothesis.Length];
bool initialised = false;
if (distilled[z] == null)
{
// create a new distilled particle
distilled[z] = new particleGridCellBase();
distilled[z].colour = new byte[3];
initialised = true;
}
// update an existing distilled value
distilled[z].probabilityLogOdds += hypothesis.probabilityLogOdds;
// and update the distilled colour value
for (int col = 2; col >= 0; col--)
{
if (initialised)
distilled[z].colour[col] = hypothesis.colour[col];
else
distilled[z].colour[col] = (byte)((hypothesis.colour[col] +
distilled[z].colour[col]) / 2);
}
}
/// <summary>
/// add a new occupancy hypothesis to the list
/// for this grid cell
/// </summary>
/// <param name="h">the hypothesis to be added to this grid cell</param>
public void AddHypothesis(particleGridCell h)
{
int vertical_index = h.z;
if (Hypothesis[vertical_index] == null)
Hypothesis[vertical_index] = new List<particleGridCell>();
Hypothesis[vertical_index].Add(h);
}
/// <summary>
/// add a new grid hypothesis to this pose
/// </summary>
/// <param name="hypothesis">occupancy hypothesis for a grid cell</param>
/// <param name="radius_cells">local map cache radius in cells</param>
/// <param name="grid_dimension">dimension of the occupancy grid in cells</param>
/// <param name="grid_dimension_vertical">height of the occupancy grid (z axis) in cells</param>
/// <returns>true if the hypothesis was added</returns>
public bool AddHypothesis(
particleGridCell hypothesis,
int radius_cells,
int grid_dimension,
int grid_dimension_vertical)
{
bool added = false;
if (path != null)
{
added = path.Add(hypothesis, radius_cells, grid_dimension, grid_dimension_vertical);
if (added) observed_grid_cells.Add(hypothesis);
}
return (added);
}
/// <summary>
/// adds a new hypothesis to the map cache
/// </summary>
/// <param name="hypothesis">grid hypothesis to be added</param>
/// <param name="radius_cells">radius of the local map cache</param>
/// <param name="grid_dimension">dimension of the occupancy grid</param>
/// <param name="grid_dimension_vertical">height of the occupancy grid (z axis) in cells</param>
/// <returns>true if the hypothesis was added</returns>
public bool Add(particleGridCell hypothesis,
int radius_cells,
int grid_dimension,
int grid_dimension_vertical)
{
bool added = true;
// create a new list for this grid coordinate if necessary
// allocating memory as its needed for each grid dimension
// is far more efficient than just allocating a big three
// dimensional chunk in one go
if (map_cache == null)
{
// store the top left position of the map cache
map_cache_tx = hypothesis.x - radius_cells;
map_cache_ty = hypothesis.y - radius_cells;
// store the width of the map cache
map_cache_width_cells = radius_cells * 2;
map_cache = new List<particleGridCell>[map_cache_width_cells][][];
}
// get the x,y coordinate within the map cache
int x = hypothesis.x - map_cache_tx;
int y = hypothesis.y - map_cache_ty;
if (((x < 0) || (x >= map_cache_width_cells)) ||
((y < 0) || (y >= map_cache_width_cells)))
{
// we're outside of the cache
added = false;
//resize_map_cache(x, y);
}
else
{
// add the hypothesis to the cache map
int z = hypothesis.z;
// create new lists as they are needed
if (map_cache[x] == null)
map_cache[x] = new List<particleGridCell>[map_cache_width_cells][];
if (map_cache[x][y] == null)
map_cache[x][y] = new List<particleGridCell>[grid_dimension_vertical];
if (map_cache[x][y][z] == null)
map_cache[x][y][z] = new List<particleGridCell>();
// add to the list
map_cache[x][y][z].Add(hypothesis);
}
return (added);
}