I developed this software as part of my studies. Some of it I wrote for a university project, others I wrote for my master thesis.


EDoHa, short for Evidence Detection fOr Hypothesis vAlidation, is an annotation tool on top of the INCEpTION platform. Its goal is to support researchers in doing qualitative research, such as analysing interviews or other forms of text. To do so, it offers two views in which a user can label sentences and link them to self-defined groups. Furthermore, EDoHa can learn from a user in what kind of sentences they are interested in and to which group a labeled sentence belongs.


This reinforcement learning framework is based on the reinforcement learning framework I build for my masterthesis. It combines multilayer perceptron with the forwards kinematics engine to allow a learner to learn how the reach for a arbitrary target. Hence the acronym Reinforcement Learning to Reach (RLtR).

Currently it supports using reinforcement learning to learn the inverse kinematics of a two DoF robotic arm. It still work in progress and the examples may not work perfectly.

You can find the documentation here.


This small package is my implementation of a Multilayer Perceptron (MLP). It is fairly small and should be easy to use.

Of course, you can also download the Source package and browse the documentation.

Forward Kinematics

I also implemented a small forward kinematics engine which contains all necessary operations for rotationally transformations. It can transform any 3 dimensional position from the shoulder’s coordinate system to the end-effector’s one and back.

Its test class also demonstrates the usage.

Communication Framework

I developed this simple communication framework in Java for a university project in which we wanted several robots to look for and collect coloured barrels. This project, as well as the behaviour depend on additional projects, which I did not develop. But maybe they give someone a base for further development.

The source code is, of course, available for download and you can read the documentation.


I also developed the necessary behaviour, which is very simple for the intended task.

The source code is, of course, also available for download and you can read the documentation.