课程: 无人驾驶车辆 - PROGRAMMING A ROBOTIC CAR

Sebastian Thrun: 塞巴斯蒂安-特龙（Sebastian Thrun）是斯坦福大学从事计算机科学研究的教授、一个“谷歌人”、美国国家工程院和德国科学院成员。他以研究机器人学和机器学习而著称，尤其在无人驾驶车辆方面的工作（work with self-driving cars）。

课程描述: This class, taught by one of the foremost experts in AI, will teach you basic methods in Artificial Intelligence, including: probabilistic inference, planning and search, localization, tracking and control, all with a focus on robotics. Extensive programming examples and assignments will apply these methods in the context of building self-driving cars.

先决条件: The instructor will assume solid knowledge of programming, all programming will be in Python. Knowledge of probability and linear algebra will be helpful.

UNIT 1: Basics of probability
Monte-Carlo localization

UNIT 2: Gaussians and continuous probability
Tracking other cars with Kalman filters

UNIT 3: Car localization with particle filters

UNIT 4: Planning and search
Determining where to drive with A* search
Finding optimal routes with dynamic programming

UNIT 5: Controls
Controlling steering and speeds with PID

UNIT 6: Putting it all together
Programming a self-driving car