Let’s talk GPS. Not the “turn left at the big tree” kind that you cursed at when you missed an exit, but the kind that helps self-driving cars, drones, and anything that to navigate in free space. GPS, or Global Positioning System, is basically a constellation of satellites shouting “I’m here!” while your receiver goes, “Cool… where am I?” For humans, it’s usually “you’re five minutes away, traffic sucks, also don’t take that exit.” For machines, especially self-driving cars, it’s a vital system. The fundamental need of a GPS system is to help machines like self-driving cars to navigate.

In the previous blogs, we initially defined a robot vehicle in URDF and then defined the same vehicle using Xacros by creating templates and reusing them. In this last blog of the series (I guess), we are going to add motion to that vehicle and make it run in the virtual map. In the end, the vehicle will move like this: So let's get started: Defining the Transformation Writing the Vehicle Interface Node Configuring CMakeLists.txt and package.xml files Results What's Next Defining the Transformation In the previous post of this series, we create…

Been a while since I posted the first part in this ROS2 tutorial series, so let's start with a quick recap. In the last blog, we created a simple robotic vehicle model that looked like this: And the URDF that generated it looked something like this: <?xml version="1.0"?> <robot name="simple_vehicle"> <link name="base_link"> <visual> <origin xyz="0 0 0" rpy="0 0 0"/> <geometry> <box size="2.0 1.2 0.4"/> </geometry> <material name="red"> <color rgba="1.0 0.2 0.2 1.0"/> </material> </visual> <collision> <origin xyz="0 0 0" rpy="0 0 0"/> <geometry> <box size="2.0 1.2 0.4"/> </geometry> </collision> <inertial> <origin xyz="0 0 0" rpy="0 0 0"/> <mass value="200.0"/> <inertia ixx="16.0" iyy="66.7" izz="80.7" ixy="0" ixz="0" iyz="0"/> </inertial> </link> <!-- Left front wheel --> <link name="fl_wheel"> <visual> <origin xyz="0.0 0.0 0.0" rpy="1.5708 0 0"/> <geometry> <cylinder radius="0.3" length= "0.2"/> </geometry> <material name="black"> <color rgba="0.1 0.1 0.1 1.0"/> </material> </visual> <collision> <origin xyz="0.0 0.0 0.0" rpy="1.5708 0 0"/> <geometry> <cylinder radius="0.3" length="0.2"/> </geometry> </collision> <inertial> <mass value="10.0"/> <inertia ixx="0.45" iyy="0.45" izz="0.25" ixy="0" ixz="0" iyz="0"/> </inertial> </link> <joint name="fl_wheel_joint" type="continuous"> <parent link="base_link"/> <child link="fl_wheel"/> <origin xyz="0.9 0.8 0.0"/> </joint> <!-- Right front wheel --> <link name="fr_wheel"> <visual> <origin xyz="0.0 0.0 0.0" rpy="1.5708 0 0"/> <geometry> <cylinder radius="0.3" length= "0.2"/> </geometry> <material name="black"> <color rgba="0.1 0.1 0.1 1.0"/> </material> </visual> <collision> <origin xyz="0.0 0.0 0.0" rpy="1.5708 0 0"/> <geometry> <cylinder radius="0.3" length="0.2"/> </geometry> </collision> <inertial> <mass value="10.0"/> <inertia ixx="0.45" iyy="0.45" izz="0.25" ixy="0" ixz="0" iyz="0"/> </inertial> </link> <joint name="fr_wheel_joint" type="continuous"> <parent link="base_link"/> <child link="fr_wheel"/> <origin xyz="0.9 -0.8 0.0"/> </joint> <!-- Left rear wheel --> <link name="rl_wheel"> <visual> <origin xyz="0.0 0.0 0.0" rpy="1.5708 0 0"/> <geometry> <cylinder radius="0.3" length= "0.2"/> </geometry> <material name="black"> <color rgba="0.1 0.1 0.1 1.0"/> </material> </visual> <collision> <origin xyz="0.0 0.0 0.0" rpy="1.5708 0 0"/> <geometry> <cylinder radius="0.3" length="0.2"/> </geometry> </collision> <inertial> <mass value="10.0"/> <inertia ixx="0.45" iyy="0.45" izz="0.25" ixy="0" ixz="0" iyz="0"/> </inertial> </link> <joint name="rl_wheel_joint" type="continuous"> <parent link="base_link"/> <child link="rl_wheel"/> <origin xyz="-0.9 0.8 0.0"/> </joint> <!-- Right rear wheel --> <link name="rr_wheel"> <visual> <origin xyz="0.0 0.0 0.0" rpy="1.5708 0 0"/> <geometry> <cylinder radius="0.3" length= "0.2"/> </geometry> <material name="black"> <color rgba="0.1 0.1 0.1 1.0"/> </material> </visual> <collision> <origin xyz="0.0 0.0 0.0" rpy="1.5708 0 0"/> <geometry> <cylinder radius="0.3" length="0.2"/> </geometry> </collision> <inertial> <mass value="10.0"/> <inertia ixx="0.45" iyy="0.45" izz="0.25" ixy="0" ixz="0" iyz="0"/> </inertial> </link> <joint name="rr_wheel_joint" type="continuous"> <parent link="base_link"/> <child link="rr_wheel"/> <origin xyz="-0.9 -0.8 0.0"/> </joint> </robot>

Pathetic Programming is a series I started to build absurd programs with Python. With already two blogs in the series namely: Creating a Random Excuse Generator with Python and Are You Even a Real Python Programmer? Take This Useless Quiz to Find Out, I thought it was now time for the third one. And this time, we are making our code talk back to us.

In ROS2, if you have ever worked with coordinate transformations, you’ve likely encountered the acronym URDF at some point. It stands for Unified Robot Description Format. Sounds formal, almost intimidating, doesn’t it? Yet behind that technical name lies something surprisingly straightforward and incredibly powerful—the way ROS2 understands what your robot looks like, how its parts fit together, and how they move. Think of URDF as the architectural blueprint for your robot’s digital twin. Without it, ROS2 can’t simulate your creation, visualize it, or plan its movements effectively. Whether you’re working on a robotic arm, a wheeled rover, or a complex humanoid, URDF is the essential language that bridges mechanical design with software.

If you’ve ever tried to explain Bayes’ theorem to someone at a party, you know the look you get. That glazed-over, polite nod that says “I’ll remember your name but not a single word you just said.” And yet, Bayes’ theorem is one of those quietly powerful tools in the machine learning toolbox that’s simultaneously simple, annoyingly subtle, and sneakily everywhere. To warm you up, let’s start with the simple example. Imagine you go to the doctor for a routine check-up, and they run a screening test for a rare condition.

Explore the world of image processing using Python with our comprehensive guide. Dive into hands-on exercises that cover key techniques, from basic manipulations to advanced transformations. Elevate y...

You know how some people like to claim that the math we learn in high school has no real-world use? That it’s just a bunch of abstract equations you’ll never see again once you start working? Well, next time you hear someone say that, send them a link to this blog — because here’s a perfect counterexample. Story time! I’m currently working on a project that requires knowledge of the steering angle of a vehicle — a crucial parameter for several control and planning tasks. However, this value isn’t directly available on the…

I had a Raspberry Pi lying around and wanted to do something actually useful with it—something more exciting than just another media server or a blinking LED project. So, naturally, I decided to build my own WireGuard VPN server at home. The goal? To access my entire home network securely from anywhere in the world, whether I’m on dodgy public Wi-Fi or just out and about. Turns out, setting up a VPN on a Pi is way easier than it sounds, and it opens up a world of possibilities—from grabbing files on my laptop to tinkering with projects remotely.

YouTube video by Christian Lempa

You were probably supposed to be working on that feature ticket you promised your PM three sprints ago. But here you are, elbow-deep in convolutional layers, trying to make your dog look like a Monet painting. Bravo. In this project, you’ll take two images — this “content” image (of a donkey on a horse) and this “style” image (Van Gogh’s Starry Night) — and you’ll smash them together until the result looks something like this: Content + Style = Output that might trick your mom into thinking you’re an artist.

Because nothing says “I’m an adult with responsibilities” like spending four hours cartoonifying your own face. Let’s be honest. At some point between debugging spaghetti code and microwaving yesterday’s coffee, we’ve all wondered: "What if I looked like a cartoon character?" You know, those smooth-skinned, big-eyed, endlessly expressive people who clearly don’t have to deal with legacy CSS or Jira tickets.

Imagine you're trying to follow a Formula 1 car as it races around a track. You don't care where the car started—you just want to keep your eyes glued to it as it zooms around corners. Now think of doing that with a computer, but instead of eyes, it has a camera. That's what object tracking is all about, and it looks something like this: