Robotics and research background with industry experience, interested in building work around sustainable agriculture, food systems, and real-world impact.
Overview
7
7
years of professional experience
3
3
Certifications
2
2
Languages
Work History
Research Engineer (PhD Student - Incomplete)
John Deere Research
01.2021 - 02.2023
As a researcher at John Deere, my responsibilities include project management and participation in interdisciplinary research within a publicly funded project. - "Nachhaltige Landwirtschaft Mit KI".
My role involved deriving user stories and application scenarios based on the requirements of stakeholders. The primary focus was to explore the utilization of autonomous/semi-autonomous vehicles for row guidance (AutoTrac Vision 2.0) and broadcast precision spraying applications.
Collaborated closely with research partners from RPTU, DFKI and Fraunhofer to consolidate research findings and played a pivotal role in achieving project objectives.
It also involved summarizing and documenting research findings, considering the perspective of the OEM among our research partners.
Additionally, conducted extensive research on the utilization of a robot prototype (ROS/ROS2) for phenotyping, data collection, and evaluation of sensor(s) positioning in agricultural applications.
Tools: [ROS/ROS2, JIRA, Microsoft Visio]
Skills: Product Development, Research, Leadership, Data analytics, Simulation Modeling, 3D Modeling, Robotics and AI
John Deere Research [European Technology Innovation Center]
Master Thesis
John Deere Research and RPTU Kaiserslautern
11.2019 - 12.2020
Title: "Evaluation of Virtual Environments and Architectures for Highly Automated Agricultural Machinery Using Machine Learning Methods"
Design and development of real-time simulation environments from scratch for highly automated agricultural vehicles.
Planning, designing, and developing real-world 3D models and AG vehicles in the Unreal Engine while concurrently integrating the ROS framework.
Explored and evaluated advanced object detection algorithms (SSD, Faster-RCNN, YOLO) before implementing the YOLO in both simulation and real-world scenarios, utilizing synthetic data for training.
Conducted real-world experiments to evaluate the effectiveness of synthetic data in agricultural contexts.
Developed and executed test cases to validate perception algorithms within ROS for the healthcare robot, specifically the Care-o-Bot-4.
Created Behavioral Trees and conducted testing within the Groot GUI.
Designed and implemented US sensor drivers and integrated them into the existing ROS framework of Care-O-Bot-4.
Tools: [ROS, Python, C++, Qt, GIT, Groot]
Industrial Project Work (Projektarbeit)
Continental AG
06.2018 - 12.2018
Developed and integrated Linear Drive interface tool with GUI into an anechoic radar chamber for design verification of radar sensors.
Model-Based Systems Engineering (MBSE): Performed verification and validation of radar sensor functional software in Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) workbench environments, ensuring compliance with requirements documented in DOORS.