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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Showing 10 of 31 repositories
- OcclusionAwareMotionPlanning Public
TUM-AVS/OcclusionAwareMotionPlanning’s past year of commit activity - RBFN-Motion-Primitives Public
TUM-AVS/RBFN-Motion-Primitives’s past year of commit activity - GGGVDiagrams Public
Tool to generate g-g and g-g-g-v diagrams for vehicle model analysis and autonomous driving trajectory planning functions
TUM-AVS/GGGVDiagrams’s past year of commit activity - TUM-CONTROL Public
TUM-AVS/TUM-CONTROL’s past year of commit activity - F1TENTH-Auxiliaries Public
The F1TENTH_Auxiliaries repository is a collection of essential helper tools and resources created to facilitate the experience of working with F1TENTH autonomous racing cars
TUM-AVS/F1TENTH-Auxiliaries’s past year of commit activity - F1TENTH-lab_ws Public
This repository contains a fully functioning image of all packages necessary for the practical course: "F1TENTH: Autonomous Driving Hands-on" at the Technical University of Munich
TUM-AVS/F1TENTH-lab_ws’s past year of commit activity
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