Autonomous Vehicle System and Control Architecture

C2402

Abstract
Content

This four-week virtual-only experience is conducted by leading experts in the autonomous vehicle industry and academia. You’ll develop an understanding of the fundamentals of AV architecture, including mechatronics, kinematics, and the sense-think-act framework in autonomous systems. The course builds a connection for how robotics are used in autonomous vehicles and provides you with demonstrations, procedures, and the skills necessary to program a robot with basic commands using the Robot Op

Learning Objectives
Content
At the end of this course, learners will be able to:
  • Explain ROS 2 architecture basics including pub-sub, topics, and messages
  • Describe how the mechatronics “system of systems” approach interacts with autonomous vehicle design and programming
  • Define the Sense-Think-Act in Real-Time paradigm
  • Use Sense-Think-Act to explain how an autonomous vehicle operates
  • Use ROS 2 to move an autonomous robot in a predicted path
  • Demonstrate a working autonomous robot performing basic motion and navigational tasks
  • Use Gazebo to simulate movement of a robot in a custom rudimentary world
Who Should Attend
Content

Participants will be recent graduates or new to/newly hired mechanical, electrical, and computer science engineers joining industry to support autonomous vehicle system development. The program is designed for working engineers. We also encourage those who are interested in learning more about the field of autonomous vehicles. This program will take an estimated 8-10 hours of your time on a weekly basis. This includes the two-hour live experience on Fridays, self-paced videos, as well as homework assignments.

Prerequisites
Content

Participants should have a Bachelor of Science in either mechanical, software, electrical engineering, or computer science with an interest in working on autonomous vehicles, have some coding ability in C or Python, and coursework in linear algebra and statistics.

Meta TagsDetails
Duration
13:00
CEU
3
Additional Details
Publisher
Product Code
C2402
Content Type
Instructor Led
Language
English