Robin Dietrich, M.Sc.
M.Sc. Robin Dietrich
Technische Universität München
Dienstort
Informatik 6 - Lehrstuhl für Robotik, Künstliche Intelligenz und Echtzeitsysteme (Prof. Knoll)
Work:
Parkring 11-13(8101)/II
85748 Garching b. München
- Tel.: +49 (89) 289 - 17626
- Sprechstunde: Please contact me via email to schedule an appointment.
- Raum: 8101.02.220
- robin.dietrich@tum.de
Curriculum Vitae
Robin received his bachelor's degree in Computer Science from the Hochschule Darmstadt in March 2015 and his master's degree in Computer Science from the University of Stuttgart in August 2017. Beyond that, Robin stayed at UMass Lowell (USA) for one semester during his bachelor's and studied robotics for one year at Oregon State University (USA) during his master's.
In October 2019 Robin joined the Chair of Robotics, Artificial Intelligence and Real-time Systems at the Informatics department as a research assistant. He is working on efficient signal processing of RADAR data using Spiking Neural Networks on Neuromorphic Hardware.
Thesis and Project Offers
If you are interested in a thesis or semester project position in mobile robotics and/or AI (including perception, localization, path planning, machine and deep learning) have a look at the current offers or contact me to discuss your personal preferences.
Thesis or Projects
| Type | Field / Keywords | Title | Date | |
|---|---|---|---|---|
| Open | ||||
| Ongoing | Master Thesis | Evolutionary Optimization, Spiking Neural Networks, Radar Data Clustering | Evolutionary Optimization for Spiking Neural Networks - Clustering of FMCW Radar data | 11/2022 |
| Bachelor Thesis | Neuromorphic Engineering, AI, Radar Data Processing, Object Tracking | Biologically Inspired Neuromorphic Object Tracking Using FMCW Radar Data | 09/2022 | |
| Master Thesis | Reward Based Learning, Neuromorphic Engineering, AI, Radar Data Processing | Biologically Inspired Person Following Using FMCW Radar Data | 11/2022 | |
| Master Thesis | Spiking Neural Networks, RBF Neurons, Radar Data Processing | Biologically Inspired Spiking Clustering for Autonomous Driving | 05/2022 | |
| Completed | Master Thesis | Spiking Neural Networks, Attractor Networks, Radar Data Processing | A Bio-Inspired Spiking Model for Object Tracking in FMCW-Radar Data | 02/2022 |
| Master Thesis | Multi-Robot Navigation, Safety, Path Planning | A comparative study on the ability of a mobile robot to safely navigate through diverse dynamic environments | 02/2022 | |
| Guided Research | Multi-Robot Exploration, SLAM | Co-Explore a novel multi-robot exploration metric and framework | 12/2021 | |
| Semester Thesis | Deep Learning, Object Detection, Mobile Robot | Object Detection for an Autonomous Trash Picking Robot | 05/2021 |
Teaching
| WS 2021/22 | |
| Lecture | Real-Time Systems |
|
SS 2021 | |
| Lecture | Digital Signal Processing |
| Seminar | Bio-inspired Data Processing and Learning With Neural Networks |
|
WS 2020/21 | |
| Lecture | Real-Time Systems |
| Practical Course | Intelligent Mobile Robots With ROS |
|
SS 2020 | |
| Lecture | Digital Signal Processing |
| Seminar | Bio-inspired Data Processing and Learning With Neural Networks |
|
WS 2019/20 | |
| Lecture | Real-Time Systems |
Publications
Dietrich, Robin. “Deep Learning Based Mutual Robot Detection and Relative Position Estimation.” Master-Thesis, University of Stuttgart, 2018 [Full Text PDF]
Dietrich, Robin, and Stefan Dorr. “Deep Learning-Based Mutual Detection and Collaborative Localization for Mobile Robot Fleets Using Solely 2D LIDAR Sensors,”, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019 [Full Text PDF]