Through this course, you will be able to identify key parts of self-driving cars and get to know Apollo architecture. You will be able to utilize Apollo HD Map, localization, perception, prediction, planning and control, and start the learning path of building a self-driving car.
Overview
Syllabus
- Self-Driving Overview
- Identify key parts of self-driving cars, and get to know Apollo team and architecture.
- HD Map
- Get to know how high-definition maps work, which underpin almost every other part of the software stack.
- Localization
- Practice Mock Interviews with Pramp!
- Perception
- Identify different perception tasks such as classification, detection, and segmentation and learning convolutional neural networks which are critical to perception.
- Prediction
- Study different ways to predict how other vehicles or pedestrians might move in Apollo self-driving cars.
- Planning
- Identify several different approaches Apollo uses to develop trajectories for autonomous vehicles.
- Control
- Understand how to use steering, throttle, and brake to execute our planned trajectory and master different types of controllers in Apollo.
- Congratulations
- Once completed, you’ll be provided with suggestions for future learning to pursue a self-driving car engineering career.
Taught by
Sebastian Thrun
