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
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. 🚗
Development of a virtual simulation platform for autonomous vehicle sensing, mapping, control and behaviour methods using ROS and Gazebo.
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.
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.
MPC, iLQR, Stanley, Pure Pursuit Controllers in AWSIM using ROS2
concepts + utilities + examples for prototyping/ education in mobile robotics
Integration of the perception, planning, and control subsystems of an autonomous vehicle using the Robot Operating System (ROS)
This is a simulation of an autonomous car using CARLA software as part of the final project of the course Introduction to Self driving cars by University of Toronto provided by Coursera
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