noshluk2/ROS2-Self-Driving-Car-AI-using-OpenCV

ROS2 Self Driving Car using Deeplearning and Object Tracking through openCV

49
/ 100
Emerging

This project provides a comprehensive framework for developing and testing self-driving car capabilities within a simulated environment. It takes in simulated camera feeds and sensor data, processes them using AI and computer vision techniques, and outputs control commands for a virtual car to follow lanes, recognize traffic signs, and navigate complex scenarios. It's designed for robotics engineers, AI researchers, and students interested in autonomous vehicle development.

212 stars. No commits in the last 6 months.

Use this if you are developing or learning about self-driving car algorithms and need a complete simulation environment to test lane following, traffic sign recognition, and navigation.

Not ideal if you are looking for a plug-and-play solution for a physical autonomous vehicle or a system for real-world deployment without significant adaptation.

autonomous-vehicles robotics-simulation computer-vision deep-learning-for-robotics path-planning
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 23 / 25

How are scores calculated?

Stars

212

Forks

64

Language

Python

License

MIT

Last pushed

Jul 10, 2024

Commits (30d)

0

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