Academic Resources 💻
There are no required textbooks for this course. The following is a list of optional but useful references for different parts of the course.
- Probabilistic Robotics, S. Thrun, W. Burgard, and D. Fox. MIT Press, Cambridge, MA, 2005.
- Planning Algorithms, Steven M. LaValle. Cambridge University Press.
- Artificial Intelligence: A Modern Approach (Third Edition), Russell, Stuart J., and Peter Norvig. Pearson Education Limited, 2016.
- Modeling and Control of Robot Manipulators, L. Sciavicco and B. Siciliano, Springer.
- Modern Robotics: Mechanics, Planning, and Control, Kevin M. Lynch and Frank C. Park, Cambridge University Press.
We provide you with a short and useful set of math and system primers. Math primers would be useful to brush up some of the basic concepts that you may find useful for upcoming lectures. Further, system primers will quickly take you through the tools you would need to work on the homework assignments.
- Linear Algebra and Probability fundamentals
- Basics of Linux command line
- Python fundamentals, Numpy/Matplotlib
- git & GitHub
In this course, you may need to read a lot of documentation related to Python and ROS when trying to work through the homework assignments.
Official resources for you to refer to:
Throughout the semester, if you find any external resource (especially one that isn’t linked above) particularly helpful, please let us know!