Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)
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Updated
Jan 13, 2024 - Python
Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)
A virtual simulation platform for autonomous vehicle sensing, mapping, control and behaviour methods using ROS 2 and Gazebo.
Path tracking with dynamic bicycle models
Autonomous Vehicle modelling using MATLAB and Simulink
Motion Control of Self-Driving Car for Trajectory Tracking
Lane Keeping Assist function by applying Stanley method for lateral control and PID controller for longitudinal control using Python on the Carla simulator. đźš—
A complete Python abstraction of Stanford's lateral Stanley Controller.
AV Projects with the CARLA simulator
Development of a virtual simulation platform for autonomous vehicle sensing, mapping, control and behaviour methods using ROS and Gazebo.
Development of a virtual simulation platform for autonomous vehicle sensing, mapping, control and behaviour methods using ROS and Gazebo.
This project aims to develop a vehicle controller to control the vehicle in CARLA simulator to follow a race track by navigating through preset waypoints.
This repository contains the final project work for Autonomous Driving Technologies class. Robust lane detection, Stanley control for steering, UDP communication between 2 systems, and traffic sign detectors form an autonomous navigation system.
MPC, iLQR, Stanley, Pure Pursuit Controllers in AWSIM using ROS2
stanley controller in c++
concepts + utilities + examples for prototyping/ education in mobile robotics
f1 tenth in ROS2 foxy
Integration of the perception, planning, and control subsystems of an autonomous vehicle using the Robot Operating System (ROS)
Control system for Autonomous Driving
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