Notes
for China, downloading is so slow, so i transfer this repo to Coding.net. So i suggest you turn to this link and git clone, maybe helps a lot.
Thanks
Thanks to the teachers in this courses very much !!!
I have to say that this courses surprise me a lot , as a postgraduate student aimed at working on automotive motion planning ,it is so hard to find so completed and excited sources, especially in China. So, i think it is beneficial and essential for everyone who aims at working or doing researching work on automotive. and make the decision to take the note and share the all sources of the courses.
This repository includes all the videos, subtitles and PDFs of this courses. You can download and watch it. Especially, i make a rough notebook based on the subtitles for better review. and i will step by step to complete it. Everyone can read and submit issue , i will try to replay it. Finally, hope everyone can enjoy it !!!
Class links:
- 1. Introduction to Self-Driving Cars
- 2. State Estimation and Localization for Self-Driving Cars
- 3. Visual Perception for Self-Driving Cars
- 4. Motion Planning for Self-Driving Cars
Introduction
1. Overview
Be at the forefront of the autonomous driving industry. With market researchers predicting a $42-billion market and more than 20 million self-driving cars on the road by 2025, the next big job boom is right around the corner.
This Specialization gives you a comprehensive understanding of state-of-the-art engineering practices used in the self-driving car industry. You'll get to interact with real data sets from an autonomous vehicle (AV)―all through hands-on projects using the open source simulator CARLA.
Throughout your courses, you’ll hear from industry experts who work at companies like Oxbotica and Zoox as they share insights about autonomous technology and how that is powering job growth within the field.
You’ll learn from a highly realistic driving environment that features 3D pedestrian modelling and environmental conditions. When you complete the Specialization successfully, you’ll be able to build your own self-driving software stack and be ready to apply for jobs in the autonomous vehicle industry.
It is recommended that you have some background in linear algebra, probability, statistics, calculus, physics, control theory, and Python programming. You will need these specifications in order to effectively run the CARLA simulator: Windows 7 64-bit (or later) or Ubuntu 16.04 (or later), Quad-core Intel or AMD processor (2.5 GHz or faster), NVIDIA GeForce 470 GTX or AMD Radeon 6870 HD series card or higher, 8 GB RAM, and OpenGL 3 or greater (for Linux computers).
2. Learn Objects
- Understand the detailed architecture and components of a self-driving car software stack
- Implement methods for static and dynamic object detection, localization and mapping, behaviour and maneuver planning, and vehicle control
- Use realistic vehicle physics, complete sensor suite: camera, LIDAR, GPS/INS, wheel odometry, depth map, semantic segmentation, object bounding boxes
- Demonstrate skills in CARLA and build programs with Python