SSubhnil/RacingCARLA
Learning Model Predictive Control (LMPC) for autonomous racing in CARLA 3D environment.
This program helps develop and test self-driving car algorithms in a simulated environment. It takes simulated sensor data (from cameras, LiDAR, etc.) within the CARLA 3D simulator as input and outputs optimized control commands that enable a virtual car to learn to race faster on a track. Autonomous driving researchers and engineers would use this to refine vehicle control systems.
No commits in the last 6 months.
Use this if you are developing or evaluating learning-based control systems for autonomous vehicles and need a realistic simulation environment to train and test your algorithms for high-speed driving.
Not ideal if you are looking for a simple plug-and-play solution for general autonomous navigation or if your primary interest is in areas outside of high-performance racing.
Stars
23
Forks
7
Language
Python
License
MIT
Category
Last pushed
May 25, 2021
Commits (30d)
0
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