Robot locomotion
Robotics is interdisciplinarity: whether you're into mechanics, electronics, machine learning, control theory, numerical optimization, raptor hunting, etc., it helps! The following notes connect dots between bits of knowledge I found useful for locomotion in particular. I hope they are helpful! Shoot me an email if you find anything inaccurate or imprecise (yup, accuracy and precision are not the same thing).
Where to start, you wonder? The notes below are sorted from specific to general. They assume you already know what a controller is. I imagine you've reached this page by searching for a particular topic, but if you're browsing out of curiosity that's also great :) In that case, I'd advise you stop next at the How do biped robots walk? overview.
Walking
 Capture point
 Floating base estimation
 How do biped robots walk?
 Linear inverted pendulum model
 Open loop and closed loop model predictive control
 Prototyping a walking pattern generator
Models
Contact dynamics
Dynamics
 Constrained equations of motion
 Equations of motion
 Forward dynamics
 Knee torque of a lumped mass model
 NewtonEuler equations
 Point de nonbasculement
 Principle of virtual work
 Recursive NewtonEuler algorithm
 Revolute joints
 Screw theory
 Zerotilting moment point
Kinematics
 Inverse kinematics
 Kinematics jargon
 Kinematics of a symmetric leg
 Position and coordinate systems
 Revolute joints
 Screw axes
 Screw theory
 Spatial vector algebra cheat sheet
See also
Physics

Gyroscopic precession
Experiments on angular momentum and torque.

Integration Basics
How to integrate the equations of motion.

Some comments on the structure of the dynamics of articulated motion
My goto writeup on the equations of motion.

The Principle of Least Action
A special lecture by Richard Feynman.
Optimization

An Introduction to Lagrange Multipliers
How Lagrange multipliers arise from optimization constraints.

Conversion from least squares to quadratic programming
How to go from least squares to QP, which is slightly more general.

Quadratic programming in Python
The most common class of convex problems used in optimal control.
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. I used it in my PhD and developed the pymanoid library to add wholebody inverse kinematics and model predictive control to it for prototyping humanoid walking controllers.