point_cloud_processing

This sample program is a ROS (Robot Operating System) package. It creates a ROS Node which fetches the point cloud data coming from the camera sensor and stores it into the vector of Point Clouds, using ROS Kinetic and Point Cloud Library (PCL).

Note: In this project, catkin_make build system has been used which under the hood uses cmake & make http://wiki.ros.org/catkin/commands/catkin_make

System Requirements

Ubuntu 16.04 LTS - Xenial Xerus

How to use this repo

1. Install Ubuntu 16.04 in your computer/laptop: https://ubuntu.com/tutorials/tutorial-install-ubuntu-desktop-1604#1-overview

2. Install ROS Kinetic ( this would take time!! ): [visit http://wiki.ros.org/kinetic/Installation/Ubuntu for more details]

$ sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'
$ sudo apt-key adv --keyserver 'hkp://keyserver.ubuntu.com:80' --recv-key C1CF6E31E6BADE8868B172B4F42ED6FBAB17C654
$ sudo apt-get update
$ sudo apt-get install ros-kinetic-desktop-full

3. Environment Setup: [visit http://wiki.ros.org/kinetic/Installation/Ubuntu for more details ]

$ echo "source /opt/ros/kinetic/setup.bash" >> ~/.bashrc
$ source ~/.bashrc
$ sudo apt install python-rosdep python-rosinstall python-rosinstall-generator python-wstool build-essential
$ sudo apt install python-rosdep
$ sudo rosdep init
$ rosdep update

4. Create a ROS Workspace, also known as catkin workspace:

$ source /opt/ros/kinetic/setup.bash
$ mkdir -p ~/catkin_ws/src
$ cd ~/catkin_ws/
$ catkin_make

5. Clone this repo in the `src` directory of your catkin workspace:

$ cd ~/catkin_ws/src
$ git clone https://github.com/milan-r-shah/point_cloud_processing.git

6. Compile and run:

$ cd ~/catkin_ws
$ catkin_make
$ source devel/setup.bash
$ roslaunch point_cloud_processing point_cloud_processing_node

Directory Structure

    .~/catkin_ws/src/point_cloud_processing
    |
    ├── config                          
    │   └── point_cloud_processing.yaml     # config file
    ├── data                                # Directory for storing data
    │   └── usage.txt
    ├── include
    │   └── point_cloud_processing
    │       └── point_cloud_processing.hpp  # header file - class declaration
    ├── launch
    │   └── point_cloud_processing.launch   # launch file
    ├── src
    │   ├── point_cloud_processing.cpp      # source file - class definition
    │   └── point_cloud_processing_node.cpp # contains main()
    ├── CMakeLists.txt                      # compiler instructions
    ├── package.xml                         # ROS Package Info
    └── README.md                           # README

As can be seen in the above directory structure of this repo/project, the important files are:

./package.xml :
Contains the information of this ROS package
./CMakeList.txt :
Contains the compiler instructions for compiling this ROS package
./launch/point_cloud_processing.launch :
Kind of XML file which contains instruction for launching this ROS node
./include/point_cloud_processing/point_cloud_processing.hpp :
Contains the declaration of PointCloudProcessing class, member variables, & methods
./src/point_cloud_processing.cpp :
Contains the definition of PointCloudProcessing class, member variables, & methods
./src/point_cloud_processing_node.cpp :
Contains main() where the ROS node, named node, i.e. an Object of PointCloudProcessing class is instantiated, frequency at which the data would be processed is mentioned

Class Structure

PointCloudProcessing class has public constructor, destructor, & class method runOnce() which have been declared in ./include/point_cloud_processing/point_cloud_processing.hpp
PointCloudProcessing class has different private methods as well as data members
In ./src/point_cloud_processing_node.cpp, first of all, name of the ROS node is initialized (Line No. 5); ROS NodeHandles are defined; and then an instance of class PointCloudProcessing is created: named node
In ./src/point_cloud_processing_node.cpp, there is node.runOnce() in the while loop which just displays "from runOnce()". The main magic happens by ros::spinOnce() which executes callbacks and releases the data from the camera sensor. rate.sleep() generates delay.
In ./src/point_cloud_processing.cpp, in the constructor, ROS Subscriber is initialized & so does some flag variables.
In ./src/point_cloud_processing.cpp, callback function for the ROS Subscriber is also defined.

Which Rubric points have been addressed

Loops, Fnction, I/O: The project demonstrates an understanding of C++ functions and control structures.
Line No. 13 in ./src/point_cloud_processing_node.cpp : while loop
Loops, Fnction, I/O: The project reads data from a file and process the data, or the program writes data to a file.
Line No. 10 in ./src/point_cloud_processing.cpp : reading data from external ROS Topic
Loops, Functions, I/O: The project accepts user input and processes the input. Line No. 3 & 4 in ./launch/point_cloud_processing.launch
OOP: The project uses Object Oriented Programming techniques.
Line No. 15 in ./include/point_cloud_processing/point_cloud_processing.hpp : class PointCloudProcessing
OOP: Classes use appropriate access specifiers for class members.
Line No. 17 & Line No. 22 in ./include/point_cloud_processing/point_cloud_processing.hpp
OOP: Class constructors utilize member initialization lists.
Line No. 10 & Line No. 13 in ./src/point_cloud_processing.cpp
OOP: Classes encapsulate behavior.
Line No. 10 & Line No. 27 in ./src/point_cloud_processing.cpp

milan-r-shah/point_cloud_processing