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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
What the fuss is all about…
Repository has been made private.
This website will give you some idea of what I do. Most of my projects are in C++ or Python.
This is a collection of some notes I took to learn and remember things. Notes here are no longer maintained since I’ve changed my note-taking method.
Here is a small selection of some of the projects I’ve been working on and had time to write something about. Some are more detailed than others.
Often in combination with machine learning.
Supervised, unsupervised and a little reinforcement learning. Mostly deep learning.
Mobile robots / self-driving cars: Topics like localization & sensor fusion.
Snippets with examples for common operations
Examples on how to work with iterators
How to instantiate a member vector w/ initialization lists
Understanding how to instantiate objects with the copy constructor
How it works and pitfalls
And why to use them
Pitfalls and differences to Java polymorphism
Overloading the assignment operator
Overloading for cout and other examples
Differences to Java and common pitfalls.
Explanation and examples
How to use std::vector efficiently
How to install ROS and DBW on Linux Mint or any other Ubuntu-based distro
Pitfalls when building from source and how to include/link via CMake
Make Linux use local time
A bash script to speed up the installation / configuration process.
Tested on Ubuntu 18.04
Replace stupid nautilus on Ubuntu
Sourcing .bashrc usually fails within non-interactive scripts
Use tilix as default terminal in OS and nemo
Just some examples when and how it is useful
Video of a talk @ PyCon 2018 on Python Bytecode.
Prepare SFTP connection with key-based authentication
What to do if there is no internet connection after setting up VPN.
Setup der Pihole Alternative auf Fritzbox
Cats vs. dogs Kaggle competition
Lane detection from a highway drive video.
Learning steering angle controls from camera data.
C++ implementation of a PID controller and a MPC controller for Udacity’s Self-Driving Car Simulator.
C++ implementation of a particle filter in a simulator.
Using an Unscented Kalman Filter to fuse radar and lidar data for object tracking.
Using an Extended Kalman Filter to fuse radar and lidar data for object tracking.
YOLOv2 model from the paper implemented from scratch in tensorflow.
Trajectory generation for a self-driving car w/ lane change capabilities.