ShisatoYano/AutonomousVehicleControlBeginnersGuide
Python sample codes and documents about Autonomous vehicle control algorithm. This project can be used as a technical guide book to study the algorithms and the software architectures for beginners.
Implements localization algorithms (EKF, UKF, particle filters), mapping techniques (occupancy grids, NDT, potential fields), and path planning/tracking methods (A*, RRT*, LQR, Stanley control) with interactive visualizations. Built on NumPy and SciPy, the modular architecture separates perception, planning, and control modules to demonstrate end-to-end autonomous vehicle pipelines. Cross-platform support (Linux, Windows, macOS) with Docker containerization enables consistent development environments for hands-on experimentation with classical control algorithms.
1,470 stars. Actively maintained with 27 commits in the last 30 days.
Stars
1,470
Forks
218
Language
Python
License
MIT
Category
Last pushed
Mar 20, 2026
Commits (30d)
27
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