JdeRobot/DeepLearningStudio
Collection of Deep Learning algorithms for autonomous control of vehicles on Behavior Metrics Circuits. Contains both PyTorch and Tensorflow implementations.
This collection of deep learning models helps robotics engineers and researchers quickly implement autonomous control for vehicles like cars and drones. It takes in visual data from vehicle sensors and outputs real-time steering or control commands to help the vehicle follow lanes or lines in simulated environments. It's designed for those developing or testing autonomous driving behaviors on virtual circuits.
No commits in the last 6 months.
Use this if you are a robotics engineer or researcher needing pre-built deep learning models to test and implement autonomous control for vehicles in simulated environments.
Not ideal if you are looking for ready-to-deploy, production-grade autonomous driving software for physical vehicles.
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Jupyter Notebook
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Last pushed
Jan 15, 2024
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