UT-Austin-RPL/Coopernaut
Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles
This project helps autonomous driving researchers and engineers develop and evaluate self-driving car systems. It takes in raw sensor data (like LiDAR information) from multiple vehicles and uses vehicle-to-vehicle communication to enable cooperative perception, resulting in improved driving performance, especially in challenging or dangerous situations. This tool is designed for autonomous vehicle developers focused on advanced perception and networked driving.
No commits in the last 6 months.
Use this if you are developing autonomous driving systems and want to explore or implement cooperative perception among networked vehicles to enhance safety and reliability.
Not ideal if you are working on individual vehicle autonomy without vehicle-to-vehicle communication or if your primary focus is on non-driving robotics applications.
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88
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20
Language
Jupyter Notebook
License
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Last pushed
Jul 26, 2022
Commits (30d)
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