Robotics – Technologie Hub Wien

C++ Specifiers and Attributes Cheatsheet for Embedded Systems

When creating a function for my embedded projects, I am often overwhelmed by the many possible ways to define methods or variables. Maybe this summary helps you as well! Specifiers Overview inline: For small, often-used functions. Example: High-frequency sensor data processing functions. static: For shared class members or persistent local variables. Example: Counter in a […]

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Radxa ROCK-5B Setup for ROS2 Docker

Geibinger

This tutorial should serve as quick starting guide on how to setup your Rock board. In the case of my Roboost project, I use the Rock 5B to run the Roboost-Cerebrum nodes within the Docker environment. In this post, I wrote down the steps I used to setup my environment to maybe spare someone out there

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Roboost – Primary Motor Cortex

Geibinger

In this post, I want to showcase the newest update on the Roboost software. I will give a short overview of the general changes in structure and goals and then explain the specific example application on my mecanum wheeled robot. General Updates on the Roboost Software While working on the new firmware, I had the

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micro-ROS on ESP32 [tutorial]

Geibinger

What is ROS and why would you want to run a micro version of it on an ESP32? ROS is the Robot Operating System. The naming is a bit misleading, as this is not really an operating system, but an environment and sweet of programs and tools that help to develop and run robotics applications.

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A* Path Planner for Mobile Robots

Geibinger

In this post, I want to make a little code review for a global A* planner I’ve written for a university project. I want to go through all the relevant parts of the implementation so that you can leave your suggestions for improvements in the commands. Describing the code here will also help me understand

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First Mobile Robot [mini-project]

Geibinger

In this post, I just quickly wanted to showcase my very first mobile robot. It was built for my informatics class in HTL, but I had so much fun developing it that I brought it home to continue playing with it. It uses five ultra sonic sensors to do really basic collision avoidance, controlled by

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Roboost V2

Geibinger

Version 2 of my Roboost project! As you’ve seen in the previous post, the former version had quite a few problems, although it wasn’t finished completely. So after finishing school, I decided to tackle the issue again. This time, I did not only want to do the programming, but I also wanted to learn more

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6DoF pose estimation using DOPE

Geibinger

In this article, we describe how to use DOPE, a deep neural network for 6-degree-of-freedom (6DoF) object pose estimation. We provide step-by-step instructions for installing and using DOPE to estimate the pose of objects in 3D space. This technique is useful for a variety of applications, including robotics and augmented reality.

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