ESPHome Beginner Tutorial
ESPHome is a great platform to build your own sensors for HomeAssistant!
ESPHome Beginner Tutorial Read More »
ESPHome is a great platform to build your own sensors for HomeAssistant!
ESPHome Beginner Tutorial Read More »
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
C++ Specifiers and Attributes Cheatsheet for Embedded Systems Read More »
How to safeguard your precious digital treasures from catastrophic data loss! no tech wizardry required!
3-2-1 local Backup with coldStorage [Synology Based] Read More »
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
Radxa ROCK-5B Setup for ROS2 Docker Read More »
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
Roboost – Primary Motor Cortex Read More »
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.
micro-ROS on ESP32 [tutorial] Read More »
Excelerate rapid prototyping with 2D-Printing! (also called printing)
3D-Printing with special curves [mini-project] Read More »
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.
6DoF pose estimation using DOPE Read More »