Our AVS Labs research is motivated by the goal of developing the next generation of intelligent autonomous vehicles. We aim to develop autonomous vehicles that will be able to interact with each other and with humans while operating safely, efficiently, and powerfully. On Our Github page you will find resources for teaching and research. Here you will find the algorithms, tools and simulations we developed to enable safe and trustworthy autonomy for a wide range of highly integrated autonomous vehicle applications.
TUM - Autonomous Vehicle Systems Lab
The main research at the Professorship Autonomous Vehicle Systems focusing on generating the next generation of intelligent autonomous vehicles
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Repositories
Showing 10 of 41 repositories
- RoboRacer-3DLiDAR Public
This repository contains the drivers to directly include the Livox MID-360 into the existing RoboRacer/ former F1Tenth stack.
- FM-AD-Survey Public
This repository collects research papers of large Foundation Models for Scenario Generation and Analysis in Autonomous Driving. The repository will be continuously updated to track the latest update.
- From-Words-to-Collisions Public
[ITSC'25] LLM-Guided Evaluation and Adversarial Generation of Safety-Critical Driving Scenarios
- RBFN-Motion-Primitives Public
- MultiDrive Public
MultiDrive is a co-simulation framework bridging 2D and 3D driving simulators for multi-fidelity (MF) validation of autonomous vehicle software.
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