The aim is to create ros packages and set up a small pipeline for finding objects on top of a table and offer a service for returning the position and the volume of these. For the sake of simplicity we assume that these objects are clearly separated, meaning that they are spread around the table in an orderly manner, neiter touching nor occluding each other.

Please install the system according to the instructions here: https://ai.uni-bremen.de/wiki/software/ros/installation

Before you start workin on the assignment, make sure to have completed the 'beginner level' tutorials from http://www.ros.org/wiki/ROS/Tutorials and you understand how to subscribe to a topic and create a new service and message types.

We have created a git repository for the code you will develop at:

https://github.com/ai-seminar/group-perception

Add this to your ROS workspace:

rosws set group_perception --git https://github.com/ai-seminar/group-perception.git
rosws update
source ~/.bashrc

Create the three ROS packages and as a first step commit and push the empty packages to the repository.

This package is the core of the pipeline. You need to implement three main parts here. First a subscriber to the topic where point clouds are being advertised, Then a processing module, where you work on the point cloud that you read in from the topic, and lastly the same node needs to offer a service for returning results.

As shown in the tutorial. Example code is here

Results should be returned in the message type described in the next section. Upon service call the latest results need be returned. Results are in the form of a list containing (c_centroid, c_volume) pairs, beginning with the largest in a descending order.

This package should contain all the message and service type definitions used by the perception_ and perception_client_ packages. You should define a new message type. This message should contain an ID field, a centroid,