Adding documentation

src/nodelets/obstacles_detection.cpp

@@ -73,7 +73,8 @@ public:
 		maxFloorHeight_(-1),
 		maxObstaclesHeight_(1.5),
 		waitForTransform_(false),
-		simpleSegmentation_(false)
+		simpleSegmentation_(false),
+		optimizeForCloseObject_(true)
 	{}
 
 	virtual ~ObstaclesDetection()
@@ -95,6 +96,7 @@ private:
 		pnh.param("max_floor_height", maxFloorHeight_, maxFloorHeight_);
 		pnh.param("wait_for_transform", waitForTransform_, waitForTransform_);
 		pnh.param("simple_segmentation", simpleSegmentation_, simpleSegmentation_);
+		pnh.param("optimize_for_close_object", optimizeForCloseObject_, optimizeForCloseObject_);
 
 		cloudSub_ = nh.subscribe("cloud", 1, &ObstaclesDetection::callback, this);
 
@@ -181,9 +183,7 @@ private:
 
 		ros::Time lasttime = ros::Time::now();
 
-
+		if (!simpleSegmentation_ && !optimizeForCloseObject_){
-/*
-		if (!simpleSegmentation_){
 
 			originalCloud = rtabmap::util3d::transformPointCloud(originalCloud, localTransform);
 			hypotheticalGroundCloud = rtabmap::util3d::passThrough(originalCloud, "z", std::numeric_limits<int>::min(), maxFloorHeight_);
@@ -205,8 +205,16 @@ private:
 				*obstaclesCloud += *obstaclesNearFloorCloud;
 			}
 
-		}*/
+		}
-		if (!simpleSegmentation_){
+		if (!simpleSegmentation_ && optimizeForCloseObject_){
+			// If the option optimize for close object has been set to true,
+			// we divide the floor point cloud into two subsections, one for all potential floor points up to 1m
+			// one for potential floor points further away than 1m.
+			// For the points at closer range, we use a smaller normal estimation radius and ground normal angle,
+			// which allows to detect smaller objects, without increasing the number of false positive.
+			// For all other points, we use a biger normal estimation radius (* 3.) and a bigger tolerance for the
+			// grond normal angle (* 2.).
+
 
 			originalCloud = rtabmap::util3d::transformPointCloud(originalCloud, localTransform);
 			pcl::PointCloud<pcl::PointXYZ>::Ptr originalCloud_front = rtabmap::util3d::passThrough(originalCloud, "x", std::numeric_limits<int>::min(), 1.);
@@ -306,6 +314,7 @@ private:
 	double maxFloorHeight_;
 	bool waitForTransform_;
 	bool simpleSegmentation_;
+	bool optimizeForCloseObject_;
 
 	tf::TransformListener tfListener_;
 

src/nodelets/point_cloud_xyz.cpp

@@ -168,9 +168,8 @@ private:
 			}
 
 			if (special_filter_close_object_){
-				cv::Mat pRoi = image(cv::Rect(int(0.05*(float(cols))),int(0.05*(float(rows))),int(0.9*(float(cols))),int(0.9*float(rows))));
+				//cv::Mat pRoi = image(cv::Rect(int(0.05*(float(cols))),int(0.05*(float(rows))),int(0.9*(float(cols))),int(0.9*float(rows))));
-				//cv::GaussianBlur(pRoi, pRoi, cv::Size(3, 3), 0, 0);
+				//cv::medianBlur(pRoi, pRoi, 3);
-				cv::medianBlur(pRoi, pRoi, 3);
 
 				//Do filter of close objects
 				pRoi = image(cv::Rect(int(cols/10),int(0.8*(float(rows))),int(0.8*(float(cols))),int(0.15*float(rows))));
@@ -187,9 +186,6 @@ private:
 					}
 			}
 
-
-
-
 			image_geometry::PinholeCameraModel model;
 			model.fromCameraInfo(*cameraInfo);
 			float fx = model.fx();