Advanced Dynamics

The field of robotics can be largerly subdivided into physical system design and construction and robotic system modeling and use. For robotic system deployment, a robot must see (percieve) its environment, think (model and plan) and act (control) in order to navigate or interact successfully in a task. A key component of this process is modeling as a precursur to planning and control. Robots should be able to model how they will move in the presence of external forces and how objects they are interacting with or observing are expected to move.

This course studies how rigid bodies move under the presence of forces (dynamics) and investigates the most efficient analytical representations of this motion for both simple and complex geometries towards applications of system modeling, planning and control.

Modeling and analysis of dynamical systems. This class will cover reference frames and coordinate systems, kinematics and constraints, mass distribution, virtual work, D'Alembert's principle, Lagrange, and Hamiltonian equations of motion.

We will then consider select topics in controls and machine learning that utilize dynamics concepts. Students will learn and apply these concepts through homework and projects involving dynamic systems simulation.

You Will Learn

  • To reason about a system's dynamical model and analytically represent the model.
  • Given a dynamical model, design a control law that produces the expected behavior with analysis for guarantees (stability).
  • To apply system identification techniques for approximating (partially observable) models and apply control techniques with this identification.

Course Page
$4,200.00 Subject to change
Online, instructor-led
10 weeks, 10-20 hrs/week
Robotics and Autonomous Systems Graduate Certificate Introduction to Mechanical Engineering Graduate Certificate
Stanford School of Engineering