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 the neural basis of localization and mapping in mammlian brains in order to use recent findings from neuroscience to build new algorithms for mobile robot navigation. His work is specifically focused on the identification and analysis of temporal dynamics in the hippocampus and its potential application in a neuromorphic SLAM.

Thesis and Project Offers

If you are interested in a thesis or semester project position in the overlapping field of robotics, artificial intelligence and computational neuroscience then 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	Spiking Neural Networks, Egde Offloading, Autonomous Driving	Edge Offloading Strategies for Autonomous Driving Systems Using Spiking Neural Networks	10/2023

Completed	Bachelor Thesis	Spatial Cells, Spiking Neural Networks, Mobile Robot Navigation	Exploring Spatial Cell Dynamics in Spiking Neural Networks Trained on a Navigation Task	08/2023
	Master Thesis	Spiking Neural Networks, Uncertainty Quantification, Drones	Uncertainty Quantification in Spiking Neural Networks for Drone Landings	05/2022
	Master Thesis	Edge Computing, Object Detection, AMRs	Analysis of Edge Computing Offloading Strategies for Autonomous Mobile Robots	05/2023
	Master Thesis	Evolutionary Optimization, Spiking Neural Networks, Radar Data Clustering	Evolutionary Optimization for Spiking Neural Networks - Clustering of FMCW Radar data	11/2022
	Master Thesis	Reward Based Learning, Neuromorphic Engineering, AI, Radar Data Processing	Biologically Inspired Person Following Using 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	Spiking Neural Networks, RBF Neurons, Radar Data Processing	Biologically Inspired Spiking Clustering for Autonomous Driving	05/2022
	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

SS 2023
Lecture	Digital Signal Processing
Seminar	Bio-inspired Data Processing and Learning With Neural Networks
WS 2022/23
Lecture	Real-Time Systems
SS 2022
Lecture	Digital Signal Processing
Seminar	Bio-inspired Data Processing and Learning With Neural Networks
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

2023
2022
2019

2023

Dietrich, Robin; Spilger, Philipp; Müller, Eric C.; Knoll, Alois C.; Schemmel, Johannes: Multi-compartment models with STDP on BrainScaleS-2. , 2023 mehr… BibTeX Volltext ( DOI )
Dietrich, Robin; Waniek, Nicolai; Stemmler, Martin; Knoll, Alois: Grid Codes versus Multi-Scale, Multi-Field Place Codes for Space. bioRxiv, 2023 mehr… BibTeX Volltext ( DOI )
Scheler, Ingo; Dietrich, Robin: coExplore: Combining multiple rankings for multi-robot exploration. , 2023 mehr… BibTeX Volltext ( DOI )

2022

López-Randulfe, Javier; Reeb, Nico; Karimi,Negin; Liu, Chen; Gonzalez, Hector A.; Dietrich, Robin; Vogginger, Bernhard; Mayr, Christian; Knoll, Alois: Time-Coded Spiking Fourier Transform in Neuromorphic Hardware. IEEE Transactions on Computers, 2022 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
Vogginger, Bernhard; Kreutz, Felix; López-Randulfe, Javier; Liu, Chen; Dietrich, Robin; Gonzalez, Hector A; Scholz, Daniel; Reeb, Nico; Auge, Daniel; Hille, Julian; Arsalan, Muhammad; Mirus, Florian; Grassmann, Cyprian; Knoll, Alois; Mayr, Christian: Automotive Radar Processing With Spiking Neural Networks: Concepts and Challenges. Frontiers in Neuroscience, 2022 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)

2019

Dietrich, Robin; Dorr, Stefan: Deep Learning-Based Mutual Detection and Collaborative Localization for Mobile Robot Fleets Using Solely 2D LIDAR Sensors. 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, 2019 mehr… BibTeX Volltext ( DOI )