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--- teaching:se-kiba:perception-assignment [2013/05/01 14:25] – [Homework: ROS packages for perception] balintbe
+++ teaching:se-kiba:perception-assignment [2016/05/19 09:19] (current) – external edit 127.0.0.1
@@ Line 21: / Line 21: @@
 Create the three ROS packages and as a first step commit and push the empty packages to the repository.
+Download the bag file from this [[https://ai.uni-bremen.de/public/kiba_pointcloud.bag|link]].
 ====== Package Descriptions ======
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 ====Processing the cloud====
-Point Clouds should be processed as they are read in, and the a buffer of the results should be kept in memory at all time. The purpose of the algorithm is to segment out objects lying on a table and separate each object in a separate cluster. After having done so, you are required to calculate the centroid of each cluster as well as the volume of it (all values in PCL are represented in meters.), and put these in a buffer. You will also need to advertise a service which, upon request, will always return the latest results.
+Point Clouds should be processed as they are read in, and a buffer of the results should be kept in memory at all time. The processing part of the package is to segment out objects lying on a table and separate each object in a separate cluster. After having done so, you are required to calculate the centroid of each cluster as well as the volume of it (note that all values in PCL are represented in meters.), and store these in a buffer. You will need to advertise a service, which, upon request, will always return the latest results.
-Notes on segmentation:
+Notes on processing the input clouds:
   * Start from the code presented in the tutorial ([[teaching:se-kiba:perception-tutorial|Perception Tutorial]])
   * You are allowed to filter the cloud on the z axis only between 0 and 1.5 meters
   * during plane fitting using RANSAC, make sure you find the correct plane.
-  * in order to find the objects on the table create a Convex Hull and use a Prism in order to find the point above this hull.(more on this here)
+  * in order to find the objects on the table create a Convex Hull and use ExtractPolygonalPrism in order to find the points above the plane.(more on this [[http://pointclouds.org/documentation/tutorials/hull_2d.php#hull-2d|here]] and [[http://docs.pointclouds.org/trunk/classpcl_1_1_extract_polygonal_prism_data.html|here]])
-  * use Euclidean clustering with a distance threshold of 3 cm-s to find the point cluster of each object
+  * use Euclidean clustering with a distance threshold of 3 cm-s to find the point cluster of each object [[http://www.pointclouds.org/documentation/tutorials/cluster_extraction.php|link]]
---more detail to be added --
 ====Service for advertising the result====
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 ===== 3. perception_client_pkg =====
+This package implements the client side of the pipeline. It is responsible for querying the service for the latest results, and for communicating them to the users. Besides serving as the bridge between users and processing, it is also the entry point for the pipeline, meaning that it needs to offer an easy interface for launching everything that is necessary for the pipeline (roscore, openni, service subscriber etc. )
+For questions and clarifications contact //balintbe **at** tzi **dot** de//