Beispiel #1
0
        /// <summary>
        /// localise and return offset values
        /// </summary>
        /// <param name="stereo_features">disparities for each stereo camera (x,y,disparity)</param>
        /// <param name="stereo_features_colour">colour for each disparity</param>
        /// <param name="stereo_features_uncertainties">uncertainty for each disparity</param>
        /// <param name="debug_mapping_filename">optional filename used for saving debugging info</param>
        /// <param name="known_offset_x_mm">ideal x offset, if known</param>
        /// <param name="known_offset_y_mm">ideal y offset, if known</param>
        /// <param name="offset_x_mm">returned x offset</param>
        /// <param name="offset_y_mm">returned y offset</param>
        /// <param name="offset_z_mm">returned z offset</param>
        /// <param name="offset_pan_radians">returned pan</param>
        /// <param name="offset_tilt_radians">returned tilt</param>
        /// <param name="offset_roll_radians">returned roll</param>
        /// <returns>true if the localisation was valid</returns>
        public bool Localise(
            float[][] stereo_features,
            byte[][,] stereo_features_colour,
            float[][] stereo_features_uncertainties,
            string debug_mapping_filename,
            float known_offset_x_mm,
            float known_offset_y_mm,
            ref float offset_x_mm,
            ref float offset_y_mm,
            ref float offset_z_mm,
            ref float offset_pan_radians,
            ref float offset_tilt_radians,
            ref float offset_roll_radians)
        {
            int   overall_img_width  = 640;
            int   overall_img_height = 480;
            bool  valid_localisation = true;
            pos3D pose_offset        = new pos3D(0, 0, 0);
            bool  buffer_transition  = false;

            float matching_score = buffer.Localise(
                robot_geometry,
                stereo_features,
                stereo_features_colour,
                stereo_features_uncertainties,
                rnd,
                ref pose_offset,
                ref buffer_transition,
                debug_mapping_filename,
                known_offset_x_mm,
                known_offset_y_mm,
                overall_map_filename,
                ref overall_map_img,
                overall_img_width,
                overall_img_height,
                overall_map_dimension_mm,
                overall_map_centre_x_mm,
                overall_map_centre_y_mm);

            if (matching_score == occupancygridBase.NO_OCCUPANCY_EVIDENCE)
            {
                valid_localisation = false;
            }

            offset_x_mm         = pose_offset.x;
            offset_y_mm         = pose_offset.y;
            offset_z_mm         = pose_offset.z;
            offset_pan_radians  = pose_offset.pan;
            offset_tilt_radians = pose_offset.tilt;
            offset_roll_radians = pose_offset.roll;

            return(valid_localisation);
        }
        public void LocaliseAlongPath()
        {
            // systematic bias
            float bias_x_mm = -200;
            float bias_y_mm = 0;

            // number of stereo cameras on the robot's head
            int no_of_stereo_cameras = 2;

            // diameter of the robot's head
            float head_diameter_mm = 100;

            // number of stereo features per step during mapping
            int no_of_mapping_stereo_features = 300;

            // number of stereo features observed per localisation step
            int no_of_localisation_stereo_features = 100;

            string filename                  = "localise_along_path.dat";
            float  path_length_mm            = 20000;
            float  start_orientation         = 0;
            float  end_orientation           = 0; // 90 * (float)Math.PI / 180.0f;
            float  distance_between_poses_mm = 100;
            float  disparity                 = 15;

            string overall_map_filename = "overall_map.jpg";

            byte[] overall_map_img          = null;
            int    overall_img_width        = 640;
            int    overall_img_height       = 480;
            int    overall_map_dimension_mm = 0;
            int    overall_map_centre_x_mm  = 0;
            int    overall_map_centre_y_mm  = 0;

            string[] str = filename.Split('.');

            List <OdometryData> path = null;

            SavePath(
                filename,
                path_length_mm,
                start_orientation,
                end_orientation,
                distance_between_poses_mm,
                disparity,
                no_of_mapping_stereo_features,
                no_of_stereo_cameras,
                ref path);

            Assert.AreEqual(true, File.Exists(filename));
            Assert.AreEqual(true, File.Exists(str[0] + "_disparities_index.dat"));
            Assert.AreEqual(true, File.Exists(str[0] + "_disparities.dat"));

            int   no_of_grids           = 1;
            int   grid_type             = metagrid.TYPE_SIMPLE;
            int   dimension_mm          = 8000;
            int   dimension_vertical_mm = 2000;
            int   cellSize_mm           = 50;
            int   localisationRadius_mm = 8000;
            int   maxMappingRange_mm    = 10000;
            float vacancyWeighting      = 0.5f;

            metagridBuffer buffer =
                new metagridBuffer(
                    no_of_grids,
                    grid_type,
                    dimension_mm,
                    dimension_vertical_mm,
                    cellSize_mm,
                    localisationRadius_mm,
                    maxMappingRange_mm,
                    vacancyWeighting);

            buffer.LoadPath(
                filename,
                str[0] + "_disparities_index.dat",
                str[0] + "_disparities.dat",
                ref overall_map_dimension_mm,
                ref overall_map_centre_x_mm,
                ref overall_map_centre_y_mm);

            int img_width  = 640;
            int img_height = 640;

            byte[] img = new byte[img_width * img_height * 3];
            Bitmap bmp = new Bitmap(img_width, img_height, System.Drawing.Imaging.PixelFormat.Format24bppRgb);

            buffer.ShowPath(img, img_width, img_height, true, true);
            BitmapArrayConversions.updatebitmap_unsafe(img, bmp);
            bmp.Save("localise_along_path.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);

            robotGeometry geom = new robotGeometry();

            geom.CreateStereoCameras(
                no_of_stereo_cameras, 120, 0,
                320, 240,
                65,
                head_diameter_mm,
                0);

            geom.CreateSensorModels(buffer);

            Random rnd               = new Random(0);
            pos3D  pose_offset       = null;
            bool   buffer_transition = false;

            float[][] stereo_features = new float[no_of_stereo_cameras][];
            byte[][,] stereo_features_colour = new byte[no_of_stereo_cameras][, ];
            float[][] stereo_features_uncertainties = new float[no_of_stereo_cameras][];
            for (int i = 0; i < no_of_stereo_cameras; i++)
            {
                stereo_features_uncertainties[i] = new float[no_of_localisation_stereo_features];
                for (int j = 0; j < no_of_localisation_stereo_features; j++)
                {
                    stereo_features_uncertainties[i][j] = 1;
                }
            }

            float average_offset_x_mm          = 0;
            float average_offset_y_mm          = 0;
            List <OdometryData> estimated_path = new List <OdometryData>();

            int no_of_localisation_failures = 0;

            for (int i = 0; i < path.Count - 1; i += 5)
            {
                string debug_mapping_filename = "localise_along_path_map_" + i.ToString() + ".jpg";

                OdometryData p0 = path[i];
                OdometryData p1 = path[i + 1];

                // create an intermediate pose
                for (int cam = 0; cam < no_of_stereo_cameras; cam++)
                {
                    geom.pose[cam].x   = p0.x + ((p1.x - p0.x) / 2) + bias_x_mm;
                    geom.pose[cam].y   = p0.y + ((p1.y - p0.y) / 2) + bias_y_mm;
                    geom.pose[cam].z   = 0;
                    geom.pose[cam].pan = p0.orientation + ((p1.orientation - p0.orientation) / 2);

                    // create stereo features
                    int ctr = 0;
                    stereo_features[cam]        = new float[no_of_localisation_stereo_features * 3];
                    stereo_features_colour[cam] = new byte[no_of_localisation_stereo_features, 3];
                    for (int f = 0; f < no_of_localisation_stereo_features; f += 5)
                    {
                        if (f < no_of_localisation_stereo_features / 2)
                        {
                            stereo_features[cam][ctr++] = 20;
                            stereo_features[cam][ctr++] = rnd.Next(239);
                        }
                        else
                        {
                            stereo_features[cam][ctr++] = geom.image_width[cam] - 20;
                            stereo_features[cam][ctr++] = rnd.Next(239);
                        }
                        stereo_features[cam][ctr++] = disparity;
                    }
                }

                float matching_score = buffer.Localise(
                    geom,
                    stereo_features,
                    stereo_features_colour,
                    stereo_features_uncertainties,
                    rnd,
                    ref pose_offset,
                    ref buffer_transition,
                    debug_mapping_filename,
                    bias_x_mm, bias_y_mm,
                    overall_map_filename,
                    ref overall_map_img,
                    overall_img_width,
                    overall_img_height,
                    overall_map_dimension_mm,
                    overall_map_centre_x_mm,
                    overall_map_centre_y_mm);

                if (matching_score != occupancygridBase.NO_OCCUPANCY_EVIDENCE)
                {
                    Console.WriteLine("pose_offset (mm): " + pose_offset.x.ToString() + ", " + pose_offset.y.ToString() + ", " + pose_offset.pan.ToString());
                    OdometryData estimated_pose = new OdometryData();
                    estimated_pose.x           = geom.pose[0].x + pose_offset.x;
                    estimated_pose.y           = geom.pose[0].y + pose_offset.y;
                    estimated_pose.orientation = geom.pose[0].pan + pose_offset.pan;
                    estimated_path.Add(estimated_pose);
                    average_offset_x_mm += pose_offset.x;
                    average_offset_y_mm += pose_offset.y;
                }
                else
                {
                    // fail!
                    no_of_localisation_failures++;
                    Console.WriteLine("Localisation failure");
                }
            }

            buffer.ShowPath(img, img_width, img_height, true, true);
            BitmapArrayConversions.updatebitmap_unsafe(img, bmp);
            bmp.Save("localisations_along_path.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);

            average_offset_x_mm /= estimated_path.Count;
            average_offset_y_mm /= estimated_path.Count;
            Console.WriteLine("Average offsets: " + average_offset_x_mm.ToString() + ", " + average_offset_y_mm.ToString());

            float diff_x_mm = Math.Abs(average_offset_x_mm - bias_x_mm);
            float diff_y_mm = Math.Abs(average_offset_y_mm - bias_y_mm);

            Assert.Less(diff_x_mm, cellSize_mm * 3 / 2, "x bias not detected");
            Assert.Less(diff_y_mm, cellSize_mm * 3 / 2, "y bias not detected");

            if (no_of_localisation_failures > 0)
            {
                Console.WriteLine("Localisation failures: " + no_of_localisation_failures.ToString());
            }
            else
            {
                Console.WriteLine("No localisation failures!");
            }
            Assert.Less(no_of_localisation_failures, 4, "Too many localisation failures");
        }