How to Install ROS on Ubuntu Linux in 5 Minutes or Less

In this post, we will get started with ROS, the Robot Operating System. ROS is the most popular robot programming platform. The reason it is so popular is that it is free, open-source, and has a ton of pre-written code that you can use for your robotics project. Sure you could write everything from scratch, but why reinvent the wheel? ROS saves you time from having to write code for common robot capabilities like navigation, motion planning, path planning, perception, control, and manipulation. It also has a huge worldwide community.

You Will Need

In order to complete this tutorial, you will need:

Ubuntu installed and running properly (I’m running my Ubuntu in a VirtualBox on Windows 10)

Directions

The official steps for installing ROS are at this link at ROS.org, but I will walk you through the process below so that you can see what each step should look like.

As of the time of this writing, the latest version with long term support (LTS) of ROS is ROS Melodic Morenia. Select that option.

I am using Ubuntu, so I will click on the Ubuntu option, which will land me on this page.

Click the 9 white dots at the bottom left of your screen.

Search for Software & Updates. Then click on it.

Make sure main, universe, restricted, and multiverse are all checked. Then click Close.

Now open up a new terminal window, and type (or copy and paste) the following command:

sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'

The command above sets your computer up to accept software from packages.ros.org.

Now we need to set up the secure keys so that our system accepts what we are going to download.

For the next step, update the package list on your system.

sudo apt update

Now type:

sudo apt-key adv --keyserver 'hkp://keyserver.ubuntu.com:80' --recv-key C1CF6E31E6BADE8868B172B4F42ED6FBAB17C654

Now do a full desktop install of ROS. At the time of this writing, the latest version is ROS Melodic Morenia. The command below installs all the software, tools, algorithms, and robot simulators for ROS. After you type the command and press Enter, press Y and hit Enter when asked if you want to continue. It will take a while to download all this stuff, so feel free to take a break while ROS downloads to your system.

sudo apt install ros-melodic-desktop-full

Now initialize rosdep. This is a tool that is required before you can use ROS.

sudo rosdep init

rosdep update

Set up the environment variables.

echo "source /opt/ros/melodic/setup.bash" >> ~/.bashrc

source ~/.bashrc

Note that anytime you want to see what environment variables ROS is using, you can type the following command:

export | grep ROS

This command will show you the ROS distribution you are using, the version of Python ROS is using, and a bunch of other stuff.

The two key variables are as follows:

ROS_MASTER_URI: Shows the URL where the roscore is in execution. This is often your own local computer.
ROS_PACKAGE_PATH: Shows the path on your computer where the ROS packages are.

Install some other tools that you will work with in ROS. After you type the command below, press Y and Enter to complete the download process.

sudo apt install python-rosinstall python-rosinstall-generator python-wstool build-essential

Here is the last step of the installation process. Check which version of ROS you have installed. If you see your ROS version as the output, congratulations you have successfully installed ROS!

rosversion -d

ROS has a lot of new vocabulary (e.g nodes, bags, topics). So before you start working with ROS, I recommend you bookmark (no need to read in detail) this page at the ROS Wiki which covers the new vocabulary associated with ROS. That way, when I mention a term you might not understand, you know where to look it up.

Pros and Cons of Gaussian Smoothing

First, before we get into the pros and cons of Gaussian smoothing, let us take a quick look at what Gaussian smoothing is and why we use it.

What is Gaussian Smoothing?

Have you ever had a photo or portrait of either yourself or someone else and wanted to smooth out the facial imperfections, pimples, pores, or wrinkles? Gaussian smoothing (also known as Gaussian blur) is one way to do this. Gaussian smoothing uses a mathematical equation called the Gaussian function to blur an image, reducing image detail and noise.

Below is an example of an image with a small and large Gaussian blur.

Image Source: Wikimedia

Pros of Gaussian Smoothing

Reduces noise in an image

Noise reduction is one of the main use cases of Gaussian smoothing.

Easy to implement

No complicated algorithms with multiple nested for loops needed. As you can see in this MATLAB implementation, Gaussian smoothing can be done with just a single line of code.

Automatic censoring

Some use cases might require you to conceal the identity of someone or to censor images that might contain material that might be inappropriate to certain audiences. Gaussian smoothing works well in these cases.

Symmetric

Gaussian smoothing produces an image that is rotationally symmetric. It is applied the same no matter what direction you go in.

Cons of Gaussian Smoothing

Lose fine image detail and contrast

If you have a use case that requires you to examine fine detail, Gaussian smoothing might make that a lot harder. An example where you might want to examine fine detail would be in a medical image or a robot trying to grasp a specific point on an object.

Does not handle “salt and pepper noise” well

Sometimes an image might have what is known as “salt-and-pepper noise.” Salt-and-pepper noise is defined as sparsely occurring white and black pixels. Below is an image showing salt-and-pepper noise.

Image Source: Wikimedia

Median filters typically do a better job than Gaussian smoothing at handling salt-and-pepper noise.

Definition of a Robot

If you ask a random roboticist to give you the definition of a robot, everyone will give you a different answer. If you do an online search, here is what you might get for the top result:

A robot is “a machine—especially one programmable by a computer— capable of carrying out a complex series of actions automatically (Wikipedia).” However, this definition falls short of what a robot really is. Just based on that definition, one could consider a dishwasher a robot. But a dishwasher is not a robot.

So back to the original topic of this post. What is a robot? The best definition of a robot I have seen is in Maja Matarić’s book, The Robotics Primer. Maja Matarić is the Director of the Robotics and Autonomous Systems Center at the University of Southern California. She received her PhD in Computer Science and Artificial Intelligence from MIT in 1994, where she studied under Rodney Brooks a founder and former Chief Technical Officer of iRobot, one of the largest consumer robotics companies in the world.

Here is Professor Matarić’s definition:

“A robot is an autonomous system which exists in the physical world, can sense its environment, and can act on it to achieve some goals.”

I love this definition.

A robot must be autonomous, which means it acts based on its own decisions.
A robot must exist in the physical world, which means it has to deal with gravity and the laws of physics just like we all do.
A robot must have sensors (look, hear, smell, and/or touch) to gather information about the world around it.
A robot must perform some computation based on what it has sensed and then act on the external world in some way. This is called the sense-think-act model, which has been the dominant paradigm for robotics for over 40 years.

Going back to the dishwasher example I mentioned earlier…a dishwasher is not a robot because it does not act on the external world. However, an autonomous robotic vacuum cleaner like the Roomba is a robot. The Roomba sucks up dirt on the floor.

So the next time you are wondering if something is a robot or just a robot wannabe, come back to this definition for clarification.