Open Student Thesis Offers

When writing your thesis at TUM I6, please follow our thesis guidelines. A guide to writing good thesis can be found here. A collection of useful material for research can be found here.

HAL4SDV - Systems Safety Security Software

HAL4SDV, or the Hardware Abstraction Layer for Software-Defined Vehicles, is a European research initiative aimed at revolutionizing the automotive industry by developing a standardized hardware-software integration framework.

This project supports the transition to Software-Defined Vehicles (SDVs), where software plays a central role in vehicle functionality, allowing for over-the-air updates, modular design, and enhanced customization.

Key goals of HAL4SDV include:

  • Creating a unified interface between vehicle hardware and software to simplify development processes.
  • Enabling faster deployment of new features and ensuring high safety and performance standards.
  • Supporting both safety-critical and general-purpose vehicle applications.
  • Enhancing collaboration across European countries to build a comprehensive SDV ecosystem.

We are looking for eager and motivated students to work on the following topics:

Application of Retrieval-Augmented Generation (RAG) Systems in Standard Compliance

We are looking for a self-motivated student to work on extracting test scenario for autonomous driving research using RAG system:

We have other open topics in the domain of Large Language Models in autonomous driving software development and we also accept open proposals or ideas with yourselves. For more information, please contact Vahid Zolfaghari.

SOW-Risk-based Safety Autonomous Driving Research

I am looking for highly self-motivated students to work on risk-based safety autonomous driving research. The topics include:

  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 1: LLM for safety-critical scenario generation for autonomous vehicles.
  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 2: Bayesian networks for real-time risk assessment in ADS.
  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 3: Risk quantification for automated driving systems based on SOTIF (ISO 21448), Responsibility Sensitive Safety (RSS), and Safety Force Field (SFF).
  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 4: Uncertainty estimation for autonomous driving perception.
  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 5: Modality-Incomplete autonomous driving perception (e.g., sensor failure).
  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 6: Autonomous driving perception based on adverse weather image restoration.

We also have several other open topics in robotics and welcome proposals or ideas from your side. For more information, please contact Dr. rer. nat. Hu Cao.

CoCoRo - Collaborative Construction Robots

[MA/GR] Intent Detection and Communication for Robots on Construction Sites

Autonomous Driving, Robotic Grasping, and Dense Prediction

I am looking for highly self-motivated students to work on projects related to autonomous driving, robotic grasping, and dense prediction (classification, detection, and segmentation). The topics include:

  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 1: Vision language model for robotic grasp pose estimation (4D and 6D).
  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 2: Object detection and semantic segmentation for autonomous driving.
  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 3: Multi-modal or multi-sensor fusion for robust object perception (2D/3D detection, segmentation, depth estimation, end-to-end autonomous driving, etc.).
  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 4: Correspondence-free absolute pose estimation algorithm (point cloud registration or globally optimal algorithms).
  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 5: Large language model and vision language model for robotics (autonomous vehicles or robotic grasping).
  • [GR/FP/IDP/SA/BA/MA/etc.] Topic 6: Medical image segmentation.

We also have several other open topics in robotics and welcome proposals or ideas from your side. For more information, please contact Dr. rer. nat. Hu Cao.

Connected Vehicles Simulations

There are a couple of interesting thesis topics in Simulation of Connected Vehicles. Feel free to write to me at nagacharan.tangirala@tum.de

  • Edge Server Placement
  • Federated Learning Simulations for Vehicles

Spiking Neural Networks - Next Generation AI for Autonomous Driving

At the KI-ASIC project we are researching about the application of bio-inspired neural networks to real-world applications.

If you are interested in learning about neuroscience and how neuromorphic engineering is trying to narrow the gap between biology an technology, do not hesitate to contact us.

Available:

Previous topics:

Whisker-Inspired Tactile Sensor and Biomimetic Rodent Robot

We aim to build a flexiable, light-weight tactile sensor based on the biological structure of rodent's vibrissae, and apply them on the robot arm, biomimetic rodent robot and other platform to provide perception and self-estimate ability.

Sensor Design and Contact Estimate:

Others:

For more information about this topic, please contact Yixuan Dang.

CeCaS: Autonomous driving - Systems and Software Engineering

As part of the research project CeCaS, a group has come up to build a new system architecture for future vehicles
with a focus on autonomous driving.

Reinforcement Learning with Diffusion Models

Simulation-Based Learning Control for Real-World Robotic Manipulation and Navigation

For more information about other available topics in reinforcement learning, data-driven control and sim2real transfer, please contact Hossein Malmir.

DeepSLAM: Deep Learning based Localization and Mapping (Vision-based Perception and Navigation)

Safe Reinforcement Learning in Single Robot and Multi-Robot Systems

We have several topics about Reinforcement Learning, Robotics,  Autonomous Driving and AI Safety, for more information, please contact Shangding Gu.

Safe Reinforcement Learning in Robotics

Currently open positions:

Additionally, we will have open topics in safe reinforcement learning for manipulators and mobile platforms in the future.
If you are interested in these topics, you can contact: jakob (dot) thumm (at) tum.de

Modular Robotics

Safe Reinforcement Learning, Multi-Agent Reinforcement Learning

Reinforcement Learning for Safe and Efficient Combustion Engine Control

Machine Learning Algorithms for Hybrid Vehicle Data

Please see this page for the available topics about 3D Object Detection and Tracking.

Autonomous Robot & Visual Servo & Deep Learning & Robot Design & Medical Robotics

For more information, please visit my homepage Mingchuan Zhou or contact me via email (zhoum@in.tum.de).

OSBORNE (Future Automotive E/E Architectures for Autonomous Cars)

We have a set of open topics in the domain of affective computing and multimodal emotion recognition, within the context of OSBORNE project, for more information please contact Sina.

Collaboration with Chair for Product Development and Lightweight Design

Low-level vision

For more information, please visit my homepage (Yuning Cui) or contact me via email (yuning.cui@in.tum.de).