ROS Autonomous Vehicles 101 Course - Python
Introduction to Autonomous Vehicles in the ROS ecosystem
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:
- What are the sensors required for an autonomous car and how to access them using ROS
- How to do autonomous navigation using a GPS
- How to create an obstacle avoider for an autonomous car
- 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
Teachers
Miguel Angel Rodriguez
Crashing engineering problems. Building solutions.
Robots used
Simulated DBW MKZ robot
Learning Path
ROS for Self-driving Cars
