开始时间: 04/22/2022 持续时间: 自主
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所在平台: Udacity 课程类别: 计算机科学 大学或机构: Udacity Self |
课程主页: https://www.udacity.com/course/cs373
课程评论: 2 个评论
Learn how to program all the major systems of a robotic car from the leader of Google and Stanford's autonomous driving teams. This class 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.
Lesson 1: Basics of probability
Monte-Carlo localization
Lesson 2: Gaussians and continuous probability
Tracking other cars with Kalman filters
Lesson 3: Car localization with particle filters
Lesson 4: Planning and search
Determining where to drive with A* search
Lesson 5: Controls
Controlling steering and speeds with PID
Lesson 6: Putting it all together
Programming a self-driving car
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大吃一惊异 2014-06-06 12:08 0 票支持; 0 票反对
这是我上的第一个mooc。对mobile robot programming的主要环节做了介绍。最大的收获就是能跟从事robotics research的基友have an intelligent conversation。可惜后来也没有做机器人的项目，所以我大概是这门课不合格的学生吧。
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wzyer 2013-05-22 15:46 0 票支持; 0 票反对
课程内容确实很偏无人驾驶车。所有的主题都是和无人驾驶车相关的。所以不算是一个AI入门的好课程。不过从移动机器人AI的主题来讲，这门课还是非常有意思的。答疑视频中也会聊到一些更深入的话题。不过总体来讲，深入的话题不多。 |
This course will cover probabilistic inference, planning and search, localization, tracking and control, all with a focus on robotics.
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