Robotics
Robotics being an interdisciplinarity activity, whether you know some signal processing, machine learning, control theory, numerical optimization, raptor hunting, etc., it helps! The following notes try to connect as many dots as possible between these useful bits of knowledge. I hope they are still a fit for younger roboticists. Shoot me an email if you find anything inaccurate or imprecise (yup, accuracy and precision are not the same thing).
Kinematics
Dynamics
 Constrained equations of motion
 Equations of motion
 Forward dynamics
 Inverse dynamics
 NewtonEuler equations
 Point de nonbasculement
 Principle of virtual work
 Screw axes
 Screw theory
 Zerotilting moment point
Contact dynamics
Walking
 Capture point
 Floating base estimation
 How do biped robots walk?
 Linear inverted pendulum model
 Prototyping a walking pattern generator
Optimization
 Conversion from least squares to quadratic programming
 Inverse kinematics
 Least squares
 Quadratic programming
Control theory
Geometry
Science
See also
Physics

Gyroscopic precession
Experiments on angular momentum and torque.

Integration Basics
How to integrate the equations of motion.

The Principle of Least Action
A special lecture by Richard Feynman.
OpenRAVE
OpenRAVE is a C++/Python robotics software for forward kinematics and inverse dynamics of robot models. It provides other features not listed here such as symbolic inverse kinematics for serial manipulators. The pymanoid library adds wholebody inverse kinematics and model predictive control on top of it to prototype humanoid walking controllers.