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 16 repositories
- IROS24_Workshop Public
TUM-AVS/IROS24_Workshop’s past year of commit activity - Frenetix-Motion-Planner Public
TUM-AVS/Frenetix-Motion-Planner’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 - CamRaDepth Public Forked from TUMFTM/CamRaDepth
Semantic Guided Depth Estimation with Transformers Using Monocular Camera and Sparse Radar
TUM-AVS/CamRaDepth’s past year of commit activity - FlexMap_Fusion Public Forked from TUMFTM/FlexMap_Fusion
ROS 2 Autoware Tool for Map Georeferencing and OSM Fusion
TUM-AVS/FlexMap_Fusion’s past year of commit activity - Frenetix-RL Public
Reinforcment Learning accelerated Motion Planning Algorithm based on Frenetix and Frenetix_Motion_Planner
TUM-AVS/Frenetix-RL’s past year of commit activity
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