Education

• Ph.D in Agricultural Robotics & Computer Vision, Technical University of Denmark, Denmark, expected 2024
• M.S. in Computer Science, University Hamburg, Germany, 2019
  • Thesis title: “Applying Deep Reinforcement Learning in the Navigation of Mobile Robots in Static and Dynamic Environments”
  • Focus: Computer Vision, Robotics, Machine Learning
• B.S. in Mechanical Engineering, University for Applied Science Hamburg, Germany, 2015
  • Thesis title: “Path Planning, self-localisation and navigating around obstacles of a mobile robot.”
  • Focus: Computational Engineering, Design, Robotics, Automation

Work experience

• 2019 - 2020: Machine Learning Engineer, Mobile Industrial Robots, Odense, Denmark
  • Focus: Multi-camera setup, object detection, sensor fusion of camera and LIDAR data
• 2016 - 2018: Technical Assistant, University for Applied Science Hamburg, Germany
  • Research project: Smart Production 4.0
  • Focus: Development of software and hardware of an autonomous mobile robot
• 2013 - 2016 Working Student:
  • University for Applied Science Hamburg, Germany
  • Research project: Azimuth systems in wind power plants

Publications

Real-Time Joint-Stem Prediction for Agricultural Robots in Grasslands Using Multi-Task Learning

Jiahao Li, Ronja Güldenring, Lazaros Nalpantidis. MDPI Agronomy, 2023

RumexWeeds: A Grassland Dataset for Agricultural Robotics

Ronja Güldenring, Frits van Evert, Lazaros Nalpantidis. Journal of Field Robotics, 2023

Lightweight Monocular Depth Estimation through Guided Decoding

Michael Rudolph, Youssef Dawoud, Ronja Güldenring, Lazaros Nalpantidis, Vasileios Belagiannis. International Conference on Robotics and Automation (ICRA), 2022

Self-supervised contrastive learning on agricultural images

Ronja Güldenring, Lazaros Nalpantidis. Journal: Computers and Electronics in Agriculture, 2021

Few-leaf Learning: Weed Segmentation in Grasslands (Finalist for the Best Paper Award on Agri-Robotics)

Ronja Güldenring, Evangelos Boukas, Ole Ravn, Lazaros Nalpantidis. International Conference on Intelligent Robots and Systems, IROS 2021

Learning Local Planners for Human-aware Navigation in Indoor Environments

Ronja Güldenring, Michael Görner, Norman Hendrich, Niels Jul Jacobsen, and Jianwei Zhang. International Conference on Intelligent Robots and Systems, IROS 2020

IT Skills

• Programming Languages: Python | C++ | Matlab
• Deep Learning Competences: Pytorch | Pytorch Lightning | Tensorflow | WandB | Tensorboard
• Relevant Libraries: Robot Operation Systems (ROS) | OpenCV
• MLOps: Git | Conda | Docker | HPC Cluster Usage
• Hardware: Nvidia Jetson | Sensor Integration
• Project Management: Jira
• Word Processing: Latex | MS Office
• IDEs: Visual Studio Code | IntelliJ IDEA

Interests

• Languages
  • German (native)
  • English (fluent)
  • Danish (advanced)
• Hobbies
  • Beachvolleyball
  • Cycling