paulvantieghem/curla
CURLA: CURL x CARLA -- Robust end-to-end Autonomous Driving by combining Contrastive Learning and Reinforcement Learning
This project helps autonomous vehicle researchers develop and test robust self-driving car agents. It takes visual data from a simulated driving environment (CARLA) and applies advanced reinforcement learning techniques to train a virtual car. The output is a highly capable autonomous driving model that can navigate complex scenarios, ideal for those researching the next generation of AI drivers.
No commits in the last 6 months.
Use this if you are an autonomous driving researcher looking to train more robust and generalizable end-to-end self-driving agents using simulated visual data.
Not ideal if you need a plug-and-play solution for real-world autonomous driving or if you don't have experience with deep reinforcement learning and simulation environments.
Stars
17
Forks
3
Language
Python
License
MIT
Category
Last pushed
Feb 06, 2024
Commits (30d)
0
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