关键信息
关于内容
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. This course is offered as part of the Georgia Tech Masters in Computer Science. The updated course includes a final project, where you must chase a runaway robot that is trying to escape!
课程大纲
Lesson 1: Localization
- Localization - Total Probability - Uniform Distribution - Probability After Sense - Normalize Distribution - Phit and Pmiss - Sum of Probabilities - Sense Function - Exact Motion - Move Function - Bayes Rule - Theorem of Total ProbabilityLesson 2: Kalman Filters
- Gaussian Intro - Variance Comparison - Maximize Gaussian - Measurement and Motion - Parameter Update - New Mean Variance - Gaussian Motion - Kalman Filter Code - Kalman Prediction - Kalman Filter Design - Kalman MatricesLesson 3: Particle Filters
- Slate Space - Belief Modality - Particle Filters - Using Robot Class - Robot World - Robot ParticlesLesson 4: Search
- Motion Planning - Compute Cost - Optimal Path - First Search Program - Expansion Grid - Dynamic Programming - Computing Value - Optimal PolicyLesson 5: PID Control
- Robot Motion - Smoothing Algorithm - Path Smoothing - Zero Data Weight - Pid Control - Proportional Control - Implement P Controller - Oscillations - Pd Controller - Systematic Bias - Pid Implementation - Parameter OptimizationLesson 6: SLAM (Simultaneous Localization and Mapping)
- Localization - Planning - Segmented Ste - Fun with Parameters - SLAM - Graph SLAM - Implementing Constraints - Adding Landmarks - Matrix Modification - Untouched Fields - Landmark Position - Confident Measurements - Implementing SLAM ###Runaway Robot Final Project教师
- Sebastian Thrun - Sebastian Thrun is a Research Professor of Computer Science at Stanford University, a Google Fellow, a member of the National Academy of Engineering and the German Academy of Sciences. Thrun is best known for his research in robotics and machine learning, specifically his work with self-driving cars.
内容设计师
佐治亚理工学院（Georgia Institute of Technology），又称佐治亚理工学院或 GT，是一所位于美国佐治亚州亚特兰大市的男女同校公立研究型大学。它是佐治亚大学系统网络的一部分。佐治亚理工学院在萨凡纳（美国佐治亚州）、梅斯（法国）、阿斯隆（爱尔兰）、上海（中国）和新加坡设有办事处。
佐治亚理工学院的工程和计算机科学课程在世界上名列前茅5,6 ，声誉卓著。此外，佐治亚理工学院还开设了科学、建筑、人文和管理课程。
平台
Udacity est une entreprise fondé par Sebastian Thrun, David Stavens, et Mike Sokolsky offrant cours en ligne ouvert et massif.
Selon Thrun, l'origine du nom Udacity vient de la volonté de l'entreprise d'être "audacieux pour vous, l'étudiant ". Bien que Udacity se concentrait à l'origine sur une offre de cours universitaires, la plateforme se concentre désormais plus sur de formations destinés aux professionnels.
