Selection of key papers

credits This list contains links and text from various online sources. See below for links to the sources

Sources

Curated list of resources

  1. Papers selected by instructor. Selection of key papers
  2. Videos curated by indstructor: Youtube cosi119a playlist
  3. Podcast about Self-Driving Deep Learning - A really good background about applying deep learning to autonomous navigation. Just 1 hour.
  4. DataCamp. This is an amazing site for learning Python and other useful Data science skills. If you are looking to brush up or learn new skills, you should definitely consider signing up!
  5. Artificial Intelligence for Robotics - A fantastic introduction to the basics of SLAM and localization, doing some of the elementary mathematics that is the foundation of this core technique in navigation.
  6. I like this overview of good Python Style. This is the official Python Style Guide
  7. Columbia edX Course on Robotics and ROS: This is an extensive and excellent course on Robotics with ROS, the Robot Operating System. I have followed it all and found that it is helpful in many different ways. You should follow the whole thing during the first 3 weeks of the course.
  8. MIT Self Driving Cars Course is a great online course consisting of lectures and other content. I recommend you purusing it!
  9. From ETH Zurich course Programming for Robots. From my review this looks like a nice video introduction and review of ROS. Here are the Slides and videos
  10. Our new Robot platform is a Turtlebot 2. Even though the number is lower, it should be more powerful and more reliable. Learning the TurtleBot and ROS is an excellent guide.