Fynn Behnke, BSc

I am an enthusiastic robotics and driverless vehicle engineer. Currently studying Master Robotics Engineering at the UAS Technikum Wien.

ABOUT ME

I'm an enthusiastic robotics engineer currently pursuing my Master's degree in Robotics Engineering at the UAS Technikum Wien. In 2023, I had the privilege of contributing to the academic discourse by publishing a paper at ARW (Austrian Robotics Workshop) 2023 as part of a project with a colleague. During my journey, I've also had the opportunity to immerse myself in the exciting realm of autonomous vehicles. I've been an integral part of the Formula Student team TU Wien Racing from 2021 to 2023, where I've gained hands-on experience with developing a driverless car.

PUBLICATIONS

This section presents the publications which have been performed as part of my study at the UAS Technikum Wien.

  • An Approach to Numerical Inverse Kinematics of Serial Manipulators using Levenberg-Marquardt Optimization 2023
    GitHub Repository
    Abstract

    Inverse kinematics for robots with high degrees of freedom require numerical approaches to approximate optimal solutions in the joint space for a desired endeffector pose. Moreover, computation of the Jacobian matrix is dependent on the configurations design parameters. The use of a mani-fold representation allows to circumvent challenges that may arise when opting for a reduced geometric form. In this work the inverse kinematic problem is approached using an on-manifold optimization scheme based on the Levenberg-Marquardt algorithm, including a technique that can be used for auto-differentiation on arbitrary serial open chains. An open-source implementation based on the Matlab robotics-toolbox is provided and tested on industrial manipulators.

PROJECTS

This section presents projects that I have been or am currently working on.