MASTER THESIS - NEUROROBOTIC PLUG INSERTION (M/W/D)
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Who are we?
fortiss is the research institute of the Free State of Bavaria for software-intensive systems and services with headquarters in Munich. The institute currently employs around 120 employees, who collaborate on research, development and transfer projects with universities and technology companies in Bavaria, Germany and Europe. Research is focused on state of the art methods, techniques and tools of software development, systems & service engineering and their application to reliable, secure cyber-physical systems, such as the Internet of Things (IoT). fortiss has the legal structure of a non-profit limited liability company (GmbH). www.fortiss.org
In the Neuromorphic Computing department, we propose a Master’s Thesis in Neurorobotics.
The background:
The fortiss Neuromoprhic Computing group has been leading efforts to implement real neurorobotic systems – that is, robots that interface with real neuromorphic hardware. These robots use orders of magnitude less energy, however they are a very new domain and, as such, they cannot yet accomplish complex tasks. Our group has previously designed a neurorobot that can insert a simple peg into a circular hole using force feedback (one of the first real neurorobot use cases in the world). We now aim to expand this to industrial plug insertion with the help of a neuromorphic camera.
In the Neuromorphic Computing department, we propose a Master’s Thesis in Neurorobotics.
The background:
The fortiss Neuromoprhic Computing group has been leading efforts to implement real neurorobotic systems – that is, robots that interface with real neuromorphic hardware. These robots use orders of magnitude less energy, however they are a very new domain and, as such, they cannot yet accomplish complex tasks. Our group has previously designed a neurorobot that can insert a simple peg into a circular hole using force feedback (one of the first real neurorobot use cases in the world). We now aim to expand this to industrial plug insertion with the help of a neuromorphic camera.
Your topic:
So far, a set of algorithms have been designed to handle the image portion of the task. In parallel, a simulated robotic arm system has been taught to approach the socket using a neuromorphic reinforcement learning algorithm. The master’s thesis will prioritize porting these elements to a real robotic arm and fine tuning the insertion. This will be initially for the simplest case but, in parallel, you will aim to robustify and connect the different sections of the image treatment process to allow for more complex situations (applying neuro-relational networks and biologically-inspired classification).
Your profile:
- Bachelor degree in computer science, electronics, machine vision or software engineering and an excellent track record in your current master’s studies
- Good skills with software development (Python, git, c++ is an asset)
- Strong experience with robotics
- Comfortable designing object oriented, modular, clean, well-documented code
- Experience with machine vision (state-of-the-art CNN, deep learning, etc.) is an asset
- Preliminary knowledge of Neuromorphic (spiking) architectures is an asset
Our offer:
- Work in partnership with world leading companies in computer technology
- Central Munich, high and modern premises with 360° view on Munich and the Alps
- Access to cutting edge robotics and neuromorphic hardware
- Enjoyable working atmosphere
- Please notice that this Master thesis is not remunerated.
Did we catch your interest?
Please submit your application with a cover letter, a detailed CV, and a current transcript of records.
Job-ID: NC_MS_2023_03
Contact: Evan Eames
Job-ID: NC_MS_2023_03
Contact: Evan Eames
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