Readings

Here I am going to keep track of papers, books, tutorials and courses that I think have interesting material. Some of the links may come from our reading group at the Mobile Robotics Lab, while others may come as a result of personal reading and searching.

Courses

Large Scale Simultaneous Inference, Bradley Efron

Programming a Robotic Car, Sebastian Thrun

Probabilistic Graphical Models, Daphne Koller

Topics in Automated Deduction, Morgan Deters

AI Planning, Execution and Learning, Manuela Veloso

Intro to Mobile Robotics, Wolfram Burgard

AI Planning, Dana Nau

AI Planning, Jim Blythe

Probabilistic analysis of algorithms, Luc Devroye

Approximate Inference in Graphical Models, David Blei

Bayesian Nonparametrics, David Blei

Foundations of probabilistic modelling, David Blei

Advanced methods in probabilistic modelling, David Blei

Advanced AI, Mike Lewicki

Fundamentals of computer vision, Mike Langer

Advanced Graph Algorithms, Tim Roughgarden

Statistical methods for machine learning and data mining, Radford Neal

Mobile robots and estimation, Paul Newman

Computer Vision, Bastian Leibe

Topics in Computer Vision, David Fleet

Algorithmic robotics and motion planning, Dan Halperin

Advanced AI, Michael Branicky

Motion planning and control under uncertainty, Kevin Lynch

Motion planning in real and virtual worlds, Dinesh Manocha

Planning in learned environments, Michael Littman

Robotic Systems, Jason O’Kane

Estimation, Ian Reid

Vision, Ian Reid

Reports on kinematics, filtering, IMUs etc, Alonzo Kelly

Electronics Tutorials

All about circuits

Socratic electronics

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