25 path-tracking algorithms are (going to be) implemented with python.

Autonomous Vehicle modelling using MATLAB and Simulink

A framework for implementing path tracking algorithms at ROS and Pyhton. Including implementations of three methods: Pure Pursuit, MPC, and LQR.

A MATLAB and Simulink project. Includes controller design, Simscape simulation, and sensor fusion for state estimation. By: Matteo Liguori; Supervisor and Collaborator: Francesco Ciriello Professor at King's College London

python-based examples of path following algorithms

pure_pursuit_planner

MPC, iLQR, Stanley, Pure Pursuit Controllers in AWSIM using ROS2

This repository contains a ROS node for autonomous lane following. The system processes camera images, applies a Bird's-Eye-View (BEV) transformation, and detects lane lines using a robust Sliding Window technique. A target path is then planned, and the Pure Pursuit algorithm calculates the necessary steering angle to guide the vehicle.

건국대학교 로봇동아리 돌밭 자율주행팀 프로젝트 (2024.09~2024.11)

Autonomous Robot Operations

Path/Speed planning, and High-Level Control modules for Formula Student Driverless

This project implements a nonlinear kinematic bicycle model for vehicle motion and evaluates multiple trajectory tracking controllers, including PID, Pure Pursuit, Stanley, MPC, and Nonlinear MPC. The controllers are developed in C++ and compared in terms of tracking accuracy, stability, and control effort across different paths, and speeds.