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In this lecture, the student will learn to model serial robots using iterative techniques. The symbolic and close form equations obtained from this process are used to model the Kinematics and Dynamics of a robot. In the second part of the course, the student will learn to use these models to design non-linear control schemes. Additionally, this lecture contains practical sessions where the student will implement several modeling and control examples using Matlab, Simulink, and ROS.

Introduction to Robot Modelling (Kinematic and Dynamic modeling). Denavit–Hartenberg methodology to describe robot joint frames, position and velocity. Robot Dynamics based on Euler-Lagrange methodology. Non-linear control for robots (Lyapunov based Analysis). Model-free control. Model-based control (robot regressor approach). Control in Operational Space. Impedance control (optional). Visual Servoing (optional). The course will be held in the English language. The materials will also be in English.

Strong Mathematical background in Linear Algebra, Trigonometry, and Calculus. Basic knowledge in robotics (preferred). Basic Knowledge in C++ and ROS All the exercises will be implemented in Matlab and ROS (ubuntu), please install in your laptop ubuntu (18.04), and ROS (Kinetic).

individual tutorial assignments: 50% individual project: 40% final presentation: 10%

Peter Corke. Robotics, Vision and Control - Fundamental Algorithms in MATLAB, volume 73 of Springer Tracts in Advanced Robotics. Springer, 2011. M.W. Spong, S. Hutchinson, and M. Vidyasagar. Robot modeling and control. John Wiley & Sons, 2006. J.J. Craig. Introduction to robotics: mechanics and control. Addison-Wesley series in electrical and computer engineering: control engineering. Pearson/Prentice Hall, 2005.