ROS Autonomous Vehicles 101 Course - Python

Introduction to Autonomous Vehicles in the ROS ecosystem

ROS Autonomous Vehicles 101 course

Course Summary

The goal of this course is to show you the basic knowledge you need to master in order to program autonomous cars for a Level 3 of autonomy.

This means, it is expected that all task should be performed autonomously, but at the same time it is expected to intervene a human driver whenever required. This level is called conditional automation.

What you will learn

In this course you are going to learn the essentials for doing autonomous cars control using ROS.

You are going to learn:

  1. What are the sensors required for an autonomous car and how to access them using ROS
  2. How to do autonomous navigation using a GPS
  3. How to create an obstacle avoider for an autonomous car
  4. How to interface ROS with a car that follows the DBW interface

Course Overview

Unit 0: Introduction

Move The car arround and know what in for you in this course

Unit 1: Sensors

Learn all the sensors you will be working with and how to visualize them in RVIZ

Unit 2: GPS Navigation

Learn the basics for GPS data use in ROS

Unit 3: Obstacles and Security

Learn to implement your own Car Security systems and obstacle detection with laser

Unit 4: CAN-Bus

Learn about CAN-Bus and how to move the car with it aswell as retrieving GPS data.

Unit 5: Microproject

Make the car move around with CAN-Bus and using the different sensors to get to the GasStation

Final recommentations

What do do next


Miguel Angel Rodriguez

Crashing engineering problems. Building solutions.

Miguel Angel Rodriguez

Robots used

Simulated DBW MKZ robot

Simulated DBW MKZ robot

Learning Path

ROS for Self-driving Cars

ROS for Self-driving Cars

Group: Advanced Robot Programming with AI

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