A collection of tutorials/books/reading lists/courses that might help.
- Tutorials
- General Tutorials
- Mini Tutorials
- Tools
- Websites
- Steve LaValle’s website.
- Arkadi Nemirovski is a big name in the convex optimization community. His website has some amazing contents including books and lecture notes on convex optimizations. I think his book and lecture notes on modern convex optimization is brilliantly unique and helpful. I am currently going through the lecture notes.
- Conference Proceedings
- Software
- Courses:
- Course of Study from CMU
- Optimization
- Robotics
- Others
- Introduction to Computing with Geometry. A good reference for Bezier curve, B-spline and NURBS.
- Books
- Optimization
- Numerical Optimization by Jorge Nocedal and Wright.
- Convex Optimization by Stephen Boyd and L. Vandenberghe.
- Motion Planning
- State Estimation
- Optimization
- Thesis PhD/Master thesis tend to be very good portals to a specific research topics. Here is a collection of what might help.
- Surveys
- An introduction on mixed-integer nonlinear optimization by Pietro Belotti et al..
- Reading Lists
- On manipulation by Nima Frazeli.
- On manipulation by Jiaji Zhou.
- Technical Writing
- Common Errors in Technical Writing by John Owens.
- LaTex Templates by Stephen Boyd.
- Mathematical Writing by Kunth et al..
Miscellaneous things sorted by subjects
Here I would like to keep a list of references not directly related to Robotics but lay the foundation of, or at least somewhat related to the algorithmic aspect of Robotics. This list will be updated irregularly.
The Art of Communication
Communication happens everywhere all the time. In his book Make it Clear, Patrick H. Winston wrote “Your success likely will be determined by how well you speak, by how well you write, and by the quality of your ideas, in that order.”
- Elements of Style: A classic guideline on how to write in English.
- Make it Clear
Numerical methods
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Numerical Linear Algebra by Trefethen and Bau is my go-to textbook on dense linear algebra solvers.
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Direct Methods for Sparse Linear Systems by Tim Davis is my go-to reference on sparse linear algebra solvers.
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I have had the pleasure to read Lloyd N. Trefethen’s Approximation Theory and Approximation Practice and Exploring ODEs. I would give my full recommendation to those who found the topics interesting.
Optimization
- Dimitri Bertsekas has a ton of amazing books and papers, but quite unfortunately I am not quite a fan of his style.
Convex Optimization
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See Convex Optimization [PDF] by S. Boyd and L. Vandenberghe for a basic overview of convex optimization. The book is clearly written and well understandable. It also has lecture videos that can be easily found on Youtube, which is a delight to watch.
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Beyond the basics, here are a few of my interests: distributed optimization, optimization on non-smooth and non-differentiable convex problems and high-speed solver implementations.
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Proximal Algorithms by Neal Parikh and Stephen Boyd.
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ADMM is an old algorithm and has seen a recent revival probably due to the need for large-scale distributed optimization. See Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers by S. Boyd et al. for a modern introduction. A talk by Boyd: link.
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There is a new book (as of September, 2020) coming up dealing with convex optimization: Algorithms for Convex Optimization by Nisheeth K. Vishnoi. I will take some time to go through the book. The author also has some interesting blogs.
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Here is a very nice explanation on the intuition of the dual problem. It is in fact the first tutorial I have seen that clearly presents what dual problem is in plain English, in constratry to tons of mathematical formulae.
Nonlinear Optimization
- See Numerical Optimization by J. Nocedal and Wright for an overview of the general optimization.
Game Physics
Computer Graphics
I am a completely freshly green new babie to the CG world, I would like to keep a list of things that helped me the most during my CG journey.