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 e-mail if you find anything inaccurate or imprecise (yup, accuracy and precision are not the same thing).
- Constrained equations of motion
- Equations of motion
- Forward dynamics
- Inverse dynamics
- Newton-Euler equations
- Point de non-basculement
- Principle of virtual work
- Screw axes
- Screw theory
- Zero-tilting moment point
- Capture point
- Floating base estimation
- How do biped robots walk?
- Linear inverted pendulum model
- Prototyping a walking pattern generator
- Conversion from least squares to quadratic programming
- Inverse kinematics
- Least squares
- Quadratic programming
Experiments on angular momentum and torque.
How to integrate the equations of motion.
The Principle of Least Action
A special lecture by Richard Feynman.
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 whole-body inverse kinematics and model predictive control on top of it to prototype humanoid walking controllers.