README.md

The Basics of Kinematic Modeling and Control of Serial-link Manipulators Using numpy

In this five-lesson tutorial, we start from the very basics of scalar and matricial operations in Python using numpy, all the way until the basics of kinematic control. Until kinematic control, most is based on [@spong2020robot].

Using this book

Each lesson is a Jupyter notebook. Each lesson can be opened and executed with popular IDEs, such as VSCode and PyCharm. The reader is expected to follow it sequentially.

Contents

Number	Title and Link	Content
1		Basic operations in Python and numpy
2		Learn about elements and operations in $\mathbb{R}^n$, $SO(n)$, and $SE(n)$ with $n\in{{2,3}}$ related to positions, orientations, and poses, respectively.
3		Learn about the composition of rigid body motion in series to obtain the forward kinematics model of a robotic manipulator, mapping their configuration space $\myvec{q}\in\mathbb{R}^n$ into their task space $\myvec{x}\in\mathbb{R}^m$.
4		Learn about the first-order differential mapping $\dot{\myvec{x}}=\mymatrix{J}\dot{\myvec{q}}$ between joint space and task space velocities through the calculation of the Jacobian $\mymatrix{J}$.
5		Employ the previous knowledge in all previous lessons to employ a Lyapunov-stable control law to move a manipulator in task space using configuration-space signals.